CN113222497B - Method for selecting address of aviation material sharing center library based on METRIC - Google Patents

Method for selecting address of aviation material sharing center library based on METRIC Download PDF

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CN113222497B
CN113222497B CN202110419311.1A CN202110419311A CN113222497B CN 113222497 B CN113222497 B CN 113222497B CN 202110419311 A CN202110419311 A CN 202110419311A CN 113222497 B CN113222497 B CN 113222497B
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王蕊
秦艺聪
孙辉
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Abstract

The invention provides a method for selecting addresses of a shipping material sharing central library based on METRIC. Determining a supply strategy of an aviation maintenance base in an addressing area based on multi-level inventory management, and establishing an addressing model of a central library of aviation spare parts based on queuing operation; setting a cost rule of the address selection model of the central repository of the marine spare parts based on the expected operation cost; and solving the address selection model of the central library of the spare parts of the aviation materials after the cost rule is set based on the particle swarm algorithm, and determining the target address of the central library of the shared aviation materials. The invention has the beneficial effects that: according to the invention, the aviation material sharing can be realized by a mode that a plurality of airlines participate in collaborative allocation together, and the spare part central library of the shared aviation material network is established for the spare parts of a certain model. The emergency transverse transfer between maintenance bases can be considered, and the aircraft parking loss is reduced to the maximum extent. The invalid competition among all airlines is reduced, the aviation material guarantee rate is improved, and the aviation material inventory redundancy is reduced, so that the operation cost of the airlines is reduced.

Description

Method for selecting address of aviation material sharing center library based on METRIC
Technical Field
The invention relates to the technical field of aviation material supply, in particular to a METRIC-based method for selecting addresses of a aviation material sharing central library.
Background
At present, the material of civil aviation aircraft is the key material resource that can normally operate in order to guarantee the design of parts such as aircraft host computer, airborne equipment and ground guarantee equipment. Under the ever-recurring and intense competitive environment of the airline market, the cost control problem becomes a significant consideration for airlines. Therefore, how to promote the sharing of the aviation materials among the airlines to realize win-win, reduce the stock redundancy and meet the requirement of the aviation material guarantee rate is the key of the current civil aircraft aviation material configuration management research, and the aviation material configuration management is an important way to realize the reasonable distribution of the aviation material stock, avoid the shortage or waste of the aviation materials, improve the aviation material utilization rate, guarantee the dispatch reliability and reduce the operation cost. Although the research on the configuration management of the aviation materials of civil aircrafts is quite abundant, from the perspective of the sharing of the aviation materials among multiple airlines, the research on the configuration management of the aviation material maintenance resources in the sharing mode is still lack of a related technical scheme.
Disclosure of Invention
The invention provides a method for selecting addresses of a shipping material sharing central library based on METRIC, which is used for solving the problem that the research on configuration management of shipping material maintenance resources in a sharing mode lacks a related technical scheme.
A method for selecting addresses of a shipping material sharing center library based on METRIC comprises the following steps:
determining a supply strategy of an aviation maintenance base in an addressing area based on multi-level inventory management, and establishing an addressing model of a central library of aviation spare parts based on queuing operation;
setting a cost rule of the address selection model of the central library of the spare parts of the aviation materials based on the expected operation cost;
and solving the address selection model of the central library of the spare parts of the aviation materials after the cost rule is set based on the particle swarm algorithm, and determining the target address of the central library of the sharing aviation materials.
Preferably, the following components: the method for determining the supply strategy of the aviation maintenance base in the addressing area based on the multilevel inventory management and establishing the addressing model of the central library of the aviation spare parts based on queuing operation comprises the following steps:
determining a dispatching strategy from a shipping material sharing center to an aviation maintenance base in the selected area according to the multi-level inventory management and the optimal ordering batch mode; wherein,
the optimal ordering batch mode is used for determining the optimal ordering quantity from the aircraft material sharing center to the aircraft maintenance base;
the commissioning strategy comprises: a longitudinal transfer strategy and a transverse transfer strategy;
the longitudinal allocation strategy is used for allocating and transporting the aviation material spare parts to the aviation maintenance base to be supplemented through the aviation material sharing center;
the transverse transfer strategy is to transfer the aviation material spare parts to be transferred through the aviation maintenance base to be transferred corresponding to the minimum transfer time;
constructing a model for the replacement operation of the aviation materials and the allocation and transportation of the spare parts according to the longitudinal allocation and transportation strategy, the transverse transportation strategy and a preset queue type FCFS service rule;
and determining a supply strategy of an aviation maintenance base in the selected area according to the model of the aeronautical material replacement operation and spare part allocation and transportation.
Preferably: the optimal ordering batch mode determines the optimal ordering quantity from the aircraft material sharing center to the aircraft maintenance base through the following formula (1):
Figure GDA0003897739870000021
wherein Q is the optimal order quantity; omega i Annual demand for the marine spare parts of the ith airline maintenance base; m is i Unit transportation cost for longitudinally transporting the aeronautical materials to the ith aviation maintenance base for the shared center of the aeronautical materials; storage c The annual storage cost of unit spare parts of the aviation materials; i =1,2,3, \8230, n; n represents the total number of airline maintenance bases.
Preferably: according to vertical allocation and transportation strategy, horizontal transfer strategy and predetermined formation type FCFS service rule construct the model of aviation material replacement operation and spare part allocation and transportation, still include:
according to the queue type FCFS service rule, the airplanes needing to be subjected to aircraft spare part replacement in the aircraft maintenance base are subjected to queue ordering according to the time sequence;
according to the queue sequencing, determining the longitudinal dispatching time of the marine material spare parts;
judging whether the queue length is larger than the total inventory number of the marine spare parts or not according to the longitudinal dispatching time; wherein,
when the queue length is larger than the total stock number of the aviation material spare parts, the requirement of the aviation maintenance base cannot be met by the stock of the aviation maintenance base, the transverse transfer strategy is started emergently to supplement the aviation material spare parts for the aviation maintenance base,
when the queue length is less than or equal to the total inventory number of the aviation spare parts, the requirement of the aviation maintenance base can be met by the inventory of the aviation maintenance base, and a longitudinal dispatching strategy is executed.
Preferably: the lateral transfer strategy further comprises:
determining priority sequencing of emergency transverse transfer of different aviation maintenance bases according to the transfer time; wherein,
the priority is determined by the replacement demand rate and the transverse transfer supply rate of spare parts of the aviation maintenance base to be supplemented;
the spare part replacement demand rate obeys poisson distribution, and is determined by the following formula (2):
Figure GDA0003897739870000031
wherein λ is ri Representing the actual replacement demand rate of the spare parts of the aircraft materials of the ith aviation maintenance base in the sharing mode, and r representing the actual value in the sharing mode; lambda [ alpha ] i Representing the replacement demand rate of the aviation spare parts of the ith aviation maintenance base in the unshared mode; { I } represents a set of nodes with the ith airline maintenance base as an emergency lateral transit point; theta represents a base node which takes the ith aviation maintenance base as an emergency transverse transit point; p θ Representing the probability of needing the spare parts of the navigation materials in the theta node; k represents the queue length of the spare parts of the aviation materials needing to be replaced; s represents the total stock quantity of the spare parts of the aviation materials; lambda [ alpha ] θ Representing the replacement demand rate of the spare parts of the navigation materials of the theta nodes in the non-sharing mode; epsilon represents the base nodes with higher priority than repair base i among all the emergency lateral transit points at the theta airline repair base; { H } represents a set of base nodes with higher priority than i among all the urgent lateral transit points of the θ node; p ε Representing the probability of needing the spare parts of the aviation materials in the aviation maintenance base epsilon; the lateral transfer supply rate is a desired value of the actual aircraft material spare part supply capacity of the aviation maintenance base to be supplemented, and is represented by the following formula (3):
Figure GDA0003897739870000032
wherein, A = P i (k≤s-1)；P i Representing the probability that the ith aviation maintenance base needs the spare parts of the aviation materials; mu.s i Indicating the supply capability of the ith airline maintenance baseExpectation; τ denotes an emergency lateral transfer point of the ith airline maintenance base; { V } represents the set of emergency lateral transfer points for the ith airline maintenance base; σ represents an advanced base node with higher priority than τ among all emergency lateral transit points of the ith airline maintenance base; { Z } represents the set of base nodes with higher priority than τ among all the emergency lateral transit points at the ith airline maintenance base; p is σ Representing the probability of needing the spare parts of the marine materials in the sigma-th advanced base node; p is τ Representing the probability of needing spare parts of the marine materials in the emergency transverse transit point tau; mu.s iτ Indicating the supply capacity expectation of the emergency lateral transfer point tau for the aircraft material spare parts of the ith airline maintenance base.
Preferably: the cost rule for setting the address selection model of the central repository of the marine material spare parts based on the operation cost expectation comprises the following steps:
acquiring the operation cost expectation, and determining a cost expectation composition; wherein,
the cost expectation components include: the method comprises the following steps of expecting the dispatching cost of spare parts of the aviation materials, expecting the loss cost when the aircraft is in a missing part stop place and expecting the storage cost of spare parts of a shared aviation material network;
determining a cost expectation value according to the cost expectation composition;
setting a cost expectation function of the address selection model of the central library of the spare parts of the aviation materials according to the cost expectation value;
and constructing a cost rule based on cost expectation according to the cost expectation function.
Preferably: the cost expectation function comprises a shipping spare part dispatching cost expectation function, a loss cost expectation function when the aircraft is out of service and stops at the place, and a shared shipping spare part network spare part storage cost expectation function; wherein,
the expected function of the distribution cost of the spare parts of the marine materials is represented by the following formula (4):
Figure GDA0003897739870000041
wherein a represents the transportation cost of the spare parts of the marine materials at a unit distance; d ic The distance between the ith aviation repair base and the aviation material sharing center library c is represented; p i (k) Representing the probability of k spare part replacement demands in the ith aviation maintenance base; d ij The distance between the ith aviation maintenance base and the jth aviation maintenance base is represented, and i is not equal to j; b = P j (k≤s-1)，P j Representing the probability of the requirement of the spare parts of the aviation materials in the jth aviation maintenance base; d = P Ω (k≤s-1)，P Ω Representing the probability of representing the requirement of the spare parts of the aviation materials in the aviation maintenance base omega; Ω represents a higher priority base node among all emergency lateral transit points of the ith airline maintenance base than the jth airline maintenance base; { N } represents the set of all emergency lateral terminal nodes for the ith airline maintenance terminal.
The expected loss cost function when the aircraft is in a missing part and stops is represented by the following formula (5):
Figure GDA0003897739870000051
wherein,
Figure GDA0003897739870000052
representing a desired rate of transportation of the turnaround voyage;
the shared aircraft material network spare part storage cost expectation function is represented by the following formula (6):
Figure GDA0003897739870000053
wherein, b is the unit storage cost of the turnover member navigation material; s i The stock of the spare parts of the aviation materials of the ith aviation maintenance base.
Preferably: the method comprises the following steps of solving an address selection model of a central library of the marine material spare parts after a cost rule is set based on a particle swarm algorithm, and determining a target address of a central library of the marine material shared, wherein the address selection model comprises the following steps:
step 1: presetting the scale pop of particles, the value range of the particle velocity v, the feasible domain range of the particles x, the maximum iteration times maxgen, the inertia weights ws and we and learning factors c1 and c2;
step 2: initializing particle population distribution X = { X1, X2, \8230;, xpop }, and iteration number iter =1;
and 3, step 3: substituting the model into a central warehouse location model of the spare parts of the marine materials, and updating pbest and gbest; wherein,
pbest represents the optimal position, and gbest represents the global historical optimal position;
and 4, step 4: updating the inertia weight w according to the iteration times, and updating the speed v and the position x of each particle according to a speed and position updating formula;
and 5: judging whether the iteration times reach the maximum iteration times maxgen, if so, skipping to the step 6, otherwise, making iter = iter +1 skip to the step 3;
step 6: and outputting the gbest as an optimal addressing point of the addressing model of the central repository, and determining a target address of the aviation material sharing central repository.
Preferably: updating the speed v and the position x of each particle according to the speed and position updating formula, wherein the speed v and the position x are represented by the following formula:
Figure GDA0003897739870000054
wherein,
Figure GDA0003897739870000055
representing the velocity of the ith particle at the iter iteration;
Figure GDA0003897739870000056
represents pbest of the ith particle in the iter iteration;
Figure GDA0003897739870000057
representing gbest in the iter iteration;
Figure GDA0003897739870000058
the current position of the ith particle in the iter iteration; w is the inertial weight; c. C 1 And c 2 Is a learning factor; r is a radical of hydrogen 1 And r 2 Are two random numbers which are independent of each other and are uniformly distributed between (0, 1).
Preferably, the following components: the updating of the inertia weight w according to the iteration number is represented by the following formula:
Figure GDA0003897739870000061
wherein, w s Representing the maximum value of the inertial weight; w is a e Representing the minimum value of the inertial weight; maxgen represents the total number of iterations; iter denotes the current number of iterations.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by the practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and drawings.
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
FIG. 1 is a flowchart of a method for selecting a location of a shipping material sharing central repository based on METRIC according to an embodiment of the present invention;
FIG. 2 is a block diagram illustrating a model for a material replacement operation and spare part allocation in an embodiment of the present invention;
FIG. 3 is a diagram illustrating a spare part provisioning strategy according to an embodiment of the present invention;
FIG. 4 is a graph of inertial weight w as a function of iteration number iter, in accordance with an embodiment of the present invention;
FIG. 5 is a graph of a linear regression of the number of take-offs and landings of an aircraft versus the number of hours of flight in an embodiment of the present invention;
FIG. 6 is a diagram of a collaborative cost expectation model for address area change in an embodiment of the present invention
FIG. 7 is a diagram of iteration numbers in accordance with an embodiment of the present invention;
FIG. 8 is a graph illustrating the cost of saving optimization as a function of the location of the site of the repository in an embodiment of the present invention;
fig. 9 is a comparison diagram of operation states of various indexes of shared and unshared aviation materials in the embodiment of the present invention.
Detailed Description
The preferred embodiments of the present invention will be described in conjunction with the accompanying drawings, and it will be understood that they are described herein for the purpose of illustration and explanation and not limitation.
Example 1:
as shown in fig. 1, the invention relates to a method for selecting addresses of a shipping material sharing center library based on METRIC, which comprises the following steps:
determining a supply strategy of an aviation maintenance base in an addressing area based on multi-level inventory management, and establishing an addressing model of a central library of aviation spare parts based on queuing operation;
setting a cost rule of the address selection model of the central library of the spare parts of the aviation materials based on the expected operation cost;
and solving the address selection model of the central library of the spare parts of the aviation materials after the cost rule is set based on the particle swarm algorithm, and determining the target address of the central library of the shared aviation materials.
The principle of the invention is as follows: the method is based on the supply strategy of sharing the aviation material spare parts by multiple airlines based on METRIC theory from the perspective of aviation material sharing, plans to establish a queuing theory-based aviation material spare part central library address selection model, and performs aviation material sharing configuration management research of multiple airlines participating in the aim of reducing the expectation of total operation cost of aviation material sharing. And then, optimizing and solving the model by adopting a particle swarm optimization algorithm with good adaptability on the computing efficiency and the processing capacity of the high-dimensional problem, and determining a target address.
The invention has the beneficial effects that: according to the invention, the aviation material sharing can be realized by a mode that a plurality of airlines participate in collaborative allocation together, and the spare part central library of the shared aviation material network is established for the spare parts of a certain model. In the process, the spare part requirements of all the participating drivers in the respective maintenance bases are considered, a shared navigation material spare part network is formed together, the central base is used for unified allocation and transportation, and the spare stock of each maintenance base is reasonably configured. When a certain maintenance base on the shared Aircraft spare part network has insufficient inventory and an Aircraft has an Aircraft on off-site (AOG), the emergency transverse transfer between the maintenance bases is considered, and the loss of the Aircraft on-site is reduced to the maximum extent. Finally, the sum of three costs including the minimized shipping spare part allocation and transportation cost, the AOG loss cost and the spare part storage cost is taken as a target, and the address of the central library of the shipping spare parts is reasonably selected. The new alliance-type development pattern of the air material distribution network is realized, invalid competition among all airlines is reduced, the air material guarantee rate is improved, the air material inventory redundancy is reduced, and therefore the operation cost of the airlines is reduced.
Example 2:
preferably: the method for determining the supply strategy of the aviation maintenance base in the addressing area based on the multilevel inventory management and establishing the addressing model of the central library of the aviation spare parts based on queuing operation comprises the following steps:
determining a dispatching strategy from a shipping material sharing center to an aviation maintenance base in the selected area according to the multi-level inventory management and the optimal ordering batch mode; wherein,
the optimal ordering batch mode is used for determining the optimal ordering quantity from the aircraft material sharing center to the aircraft maintenance base;
the dispatching strategy comprises the following steps: a longitudinal transfer strategy and a transverse transfer strategy;
the longitudinal allocation strategy is used for allocating and transporting the aviation material spare parts to the aviation maintenance base to be supplemented through the aviation material sharing center;
the transverse transfer strategy is to transfer the aviation material spare parts to be transferred through the aviation maintenance base to be transferred corresponding to the minimum transfer time;
constructing a model for the replacement operation of the aviation materials and the allocation and transportation of the spare parts according to the longitudinal allocation and transportation strategy, the transverse transportation strategy and a preset queue type FCFS service rule;
and determining a supply strategy of an aviation maintenance base in the selected area according to the model of the aeronautical material replacement operation and spare part allocation and transportation.
The principle of the invention is as follows: in order to meet the addressing requirement of the invention, the replacement operation of the marine material spare parts of each aviation base of the invention follows the first-come-first-serve rule, namely the FCFS rule, and the supplement supply of the marine material spare parts is completed by the longitudinal dispatching and the emergency transverse transportation of the central warehouse. In the process, a model for the replacement operation of the aircraft material and the allocation and transportation of spare parts is constructed, as shown in the attached figure 2. In fig. 2, k represents the queue length of spare parts to be replaced, and s represents the number of spare parts for aircraft in the airline maintenance base. Because the airplanes needing to change the turnover members are sequenced in time sequence in the airplane replacement member operation queuing system, the replacement operation of the first-in-queue is processed preferentially. After the replacement of spare parts, the spare part inventory is supplemented to an aviation maintenance base from a aviation material sharing center base by preferentially adopting a longitudinal allocation mode, and the supply strategy also reflects the demand condition and the supply condition of the spare parts of the aviation materials.
Preferably: the optimal ordering batch mode determines the optimal ordering quantity from the aircraft material sharing center to the aircraft maintenance base through the following formula (1):
Figure GDA0003897739870000081
wherein Q is the optimal order quantity; omega i Annual demand for marine material spare parts for the ith airline maintenance base; m is a unit of i The unit transportation cost for longitudinally transporting the aeronautical materials from the shared center of the aeronautical materials to the ith aviation maintenance base; storage range c The annual keeping cost of unit spare parts of the aviation materials; i =1,2,3, \8230; \ 8230n; n represents the total number of airline maintenance bases.
The invention relates to a large-scale aircraft material turnover part inventory strategy, which is characterized in that according to an aircraft material replacement operation and spare part allocation model, the most conventional mode is to use a longitudinal allocation strategy, namely allocation and transportation are carried out only through an aircraft material sharing center, and the optimal order quantity is the allocation and transportation condition which best accords with the longitudinal allocation strategy.
Example 3:
preferably: according to vertical allocation and transportation strategy, horizontal transportation strategy and predetermined formation type FCFS service rule, establish the model of building aviation material replacement operation and spare part allocation and transportation, still include:
according to the queue type FCFS service rule, the airplanes needing to be subjected to aircraft spare part replacement in the aircraft maintenance base are subjected to queue ordering according to the time sequence;
according to the queue sequencing, determining the longitudinal dispatching time of the marine material spare parts;
judging whether the queue length is larger than the total stock number of the spare parts of the aviation materials or not according to the longitudinal dispatching time; wherein,
when the queue length is larger than the total stock number of the aviation material spare parts, the requirement of the aviation maintenance base cannot be met by the stock of the aviation maintenance base, and a transverse transfer strategy is started emergently to supplement the aviation material spare parts for the aviation maintenance base;
when the queue length is less than or equal to the total inventory number of the aviation spare parts, the requirement of the aviation maintenance base can be met by the inventory of the aviation maintenance base, and a longitudinal dispatching strategy is executed.
When the method is used for constructing the model for replacing the aircraft materials and dispatching the spare parts, the aircraft material replacement demand rate of the aircraft maintenance base aircraft material spare parts can be calculated based on the longitudinal calling strategy, because the storage cost of the aircraft materials of the turnover parts is high, the demand is small, the optimal order quantity is close to 1, and the recommendation model can be calculated according to the annual average demand quantity of the aircraft materials of the turnover parts according to the method, so that the daily aircraft material replacement demand rate lambda of the aircraft maintenance base can be calculated i As shown in the following formula:
Figure GDA0003897739870000091
wherein, T FHi The annual number of hours of flight for a model in an aviation maintenance base; k is the average installed number of the turnover member aviation material on each airplane; n is the size of a certain type of fleet; t is MTBUR The average unscheduled tear-down interval for that turnaround.
In the longitudinal distribution process of the aeronautical materials: provided from a aeronautical maintenance base by a aeronautical material sharing center depotLongitudinal spare part supply rate mu i As shown in the following formula:
Figure GDA0003897739870000092
wherein d is ic The distance between the aviation material sharing central library and the aviation maintenance base is represented as i, and the distance between the aviation material sharing central library and the aviation maintenance base is represented as c;
Figure GDA0003897739870000093
is the desired transport rate of the turnaround material. The spare part inventory system of an airline maintenance base is compliant with M/M/s/∞/∞ multiple service bay models of infinite capacity and queue length, as spare part replacement requirements of the airline maintenance base can be met by its inventory. In this model, the spare part supply rate mu provided by the fuel-sharing central repository to the airline maintenance base at a time i Are all the same, i.e. satisfy mu i1 ＝μ i2 ＝…＝μ ik ＝μ i It can be seen that when the replacement of spare parts with queue length k occurs in the airline maintenance base, the supply rate of spare parts for the whole system is k mu i K =0,1,2, \ 8230;, s. Supply intensity of shipping to aviation maintenance base once by aviation material sharing central warehouse
Figure GDA0003897739870000094
Maximum supply intensity provided by aeronautical maintenance base by aeronautical material sharing central warehouse
Figure GDA0003897739870000095
In order to ensure that the queue length of spare parts waiting for replacing the aircraft materials is not longer and longer, rho should be satisfied is <1. Thus, the cumulative spare part rate C at which the demand at the airline maintenance base can be met by its own inventory i (k) Comprises the following steps:
Figure GDA0003897739870000101
therefore, the queue length of spare parts to be replaced in the aviation maintenance base is kProbability P of i (k) Comprises the following steps:
Figure GDA0003897739870000102
wherein,
Figure GDA0003897739870000103
if the payment rate is improved as much as possible according to the self requirements of the airline company, the waiting is not needed when the operation of replacing the spare parts of the aviation materials occurs, and the requirements are met:
Figure GDA0003897739870000104
the replacement requirement of spare parts at an aviation maintenance base cannot be met by self inventory, namely when the queue length k is more than or equal to s. The aeronautical material replacement demand exceeding the spare part inventory of the aviation maintenance base needs to be stopped for waiting, and the exceeding part is called a waiting queue. Thus, the probability W of a waiting queue in the airline maintenance base i (s，ρ i ) Obeying the Erlang waiting formula:
Figure GDA0003897739870000105
because the input stream of the requirement of the spare parts of the aircraft in the system is Poisson stream, the continuous random variable time T meets the non-negative condition and is T i Upper obeys a negative exponential distribution, so T has Markov properties. I.e. the process is at T (T) under the condition that the state of T (k) is known>The state at T (k)) will only be related to the state of the process at time T (k), and not to the state of the process before T (k), also referred to as no residual effect. Therefore, the probability that the waiting time T for replacing the spare parts of the aircraft materials in the aircraft maintenance base is less than or equal to ti is as follows:
Figure GDA0003897739870000106
at this time, the cumulative spare part rate C in the airline maintenance base waiting queue i (k) Comprises the following steps:
Figure GDA0003897739870000107
and the probability P of k spare part replacement demands in the airline maintenance base i (k) Comprises the following steps:
Figure GDA0003897739870000111
thus, the average wait queue length L iq Comprises the following steps:
Figure GDA0003897739870000112
in the process of transverse transportation of the aeronautical materials: we regard the airline maintenance base as a transit node, and the selection of transit node j for emergency lateral transport depends on transit time T ij The size of (2):
Figure GDA0003897739870000113
wherein d is ij The distance from the ith aviation maintenance base to the jth aviation maintenance base;
Figure GDA0003897739870000115
is the desired transport rate for the turnaround material.
The transportation cost of transporting the aviation material is:
E ij ＝a*d ij
wherein a is the transportation cost of the spare parts of the marine materials at a unit distance. The supply rate of the transverse spare parts provided by the aviation maintenance base j to the aviation maintenance base i during the emergency transverse transfer is as follows:
Figure GDA0003897739870000114
in the course of transverse transport, the invention is based on the transport time T ij Is used to determine the spare part supply strategy for the airline maintenance base, as shown in figure 3. In FIG. 3, when the aviation maintenance base i lacks the spare parts for aviation materials to apply for the urgent lateral dispatch, the minimum transit time, i.e. min (T), is selected preferentially ij ) And the corresponding node is used as a supply base j of the emergency horizontal dispatching. If the current base j has no inventory as well, then proceed to the next lowest value, and so on. Once T, because the supply capacity of the aircraft material sharing central repository is unlimited ij ≥T ic The spare parts are supplied from the aviation materials sharing center base to the aviation maintenance base by default, and other bases are not considered. As can be seen from FIG. 3, the aviation materials sharing center base represents the center base c, and the other 4 aviation maintenance bases are respectively marked with 1,2,3 and 4. For azit 1, the transit times to azit 1 according to azits 2,3,4 and the central repository c are ordered as T12 < T13 < T1c < T14. The bases 2,3 and 4 are divided into two different states according to the length of the transit time, wherein the nodes represented by the black and white interval vertical stripes represent the emergency transverse transit points of the base 1, and the nodes represented by the black dots represent the nodes which cannot be used as the emergency transverse transit points of the base 1.
Therefore, when the base 1 is short of spare parts, the base 2 firstly carries out emergency transverse transportation on the base 1, and the central warehouse c carries out longitudinal transportation on the base 2 for replenishing the stock. Only if the terminal 1 generates an emergency lateral transfer demand and the terminal 2 has no additional inventory, the terminal 3 will provide lateral transfer to the terminal 1. Accordingly, the central warehouse c carries out longitudinal allocation and inventory supplement on the base 3. If the base stations 2,3 are in a state without extra stock at the same time, the central base c supplies the base station 1 with the aircraft supplies to supplement the stock. Due to T 1c ＜T 14 The base 4 does not need to provide an emergency lateral supply to the base 1. The azits 2,3 are therefore referred to as emergency lateral transfer points for the azit 1.
Preferably: the lateral transfer strategy further comprises:
determining priority sequencing of emergency transverse transfer of different aviation maintenance bases according to the transfer time; wherein,
the priority is determined by the replacement demand rate of spare parts and the transverse transfer supply rate of the aviation maintenance base to be supplemented;
the replacement demand rate of the spare parts obeys Poisson distribution, and the replacement demand rate of the spare parts is determined by the following formula (2):
Figure GDA0003897739870000121
wherein λ is ri Representing the actual replacement demand rate of the spare parts of the aircraft materials of the ith aviation maintenance base in the sharing mode, and r representing the actual value in the sharing mode; lambda [ alpha ] i Representing the replacement demand rate of the aviation spare parts of the ith aviation maintenance base in the unshared mode; { I } represents a set of nodes with the ith airline maintenance base as an emergency lateral transit point; theta represents a base node which takes the ith aviation maintenance base as an emergency transverse transit point; p is θ Representing the probability of needing the spare parts of the navigation materials in the theta node; k represents the queue length of the spare parts of the aviation materials needing to be replaced; s represents the total stock quantity of the spare parts of the aviation materials; lambda [ alpha ] θ Representing the replacement demand rate of the spare parts of the navigation materials of the theta node in the non-sharing mode; epsilon represents a base node with higher priority than the repair base i among all the emergency lateral transit points of the theta aviation repair base; { H } represents a set of base nodes with higher priority than i among all the urgent lateral transit points of the θ node; p is ε Representing the probability of needing the spare parts of the aviation materials in the aviation maintenance base epsilon;
the lateral transfer supply rate is a desired value of the actual aircraft material spare part supply capacity of the aviation maintenance base to be supplemented, and is represented by the following formula (3):
Figure GDA0003897739870000131
wherein, A = P i (k≤s-1)；P i Representing the probability that the ith aviation maintenance base needs the spare parts of the aviation materials; mu.s i Representing the supply capacity expectation of the ith aviation maintenance base;τ denotes an emergency lateral transfer point of the ith airline maintenance base; { V } represents the set of emergency lateral transfer points for the ith airline maintenance base; σ represents an advanced base node with higher priority than τ in all the emergency lateral transit points of the ith airline maintenance base; { Z } represents the set of base nodes with higher priority than τ among all the emergency lateral transit points of the ith airline maintenance base; p is σ Representing the probability of needing the spare parts of the marine materials in the sigma-th advanced base node; p τ Representing the probability of needing spare parts of the navigation materials in the emergency transverse transit point tau; mu.s iτ Indicating the capability expectation of the emergency transshipment point tau for the supply of the marine spare parts of the ith airline maintenance base.
In the present invention: in the process of transverse transfer, the replacement demand rate of the spare parts of the aviation materials is mutually independent and accords with Poisson distribution, and the process is as follows:
X～P(λ),Y～P(μ)
then there is
Figure GDA0003897739870000132
Figure GDA0003897739870000133
I.e., Z to P (λ + μ), and thus any combination of variables that are independent of each other and obey the poisson distribution can be obtained, and still obey the poisson distribution. Therefore, the modified combined variables are also applicable to the queuing theory model.
Preferably: the cost rule for setting the address selection model of the central repository of the marine material spare parts based on the operation cost expectation comprises the following steps:
obtaining the operation cost expectation, and determining a cost expectation composition; wherein,
the cost expectation component includes: the method comprises the following steps of expecting the dispatching cost of spare parts of the aviation materials, expecting the loss cost when the aircraft is in a missing part stop place and expecting the storage cost of spare parts of a shared aviation material network;
determining a cost expectation value according to the cost expectation composition;
setting a cost expectation function of the address selection model of the central library of the spare parts of the aviation materials according to the cost expectation value;
and constructing a cost rule based on cost expectation according to the cost expectation function.
In the invention, the expectation of the shared cooperation cost of the aviation materials consists of the expectation of the dispatching cost of spare parts of the aviation materials, the expectation of the loss cost when the airplane is stopped in the absence of the spare parts and the storage cost of the spare parts of the shared aviation materials network. The cost rule is set for realizing the principle of saving cost, and accords with the original purpose of site selection of the invention, namely, cost saving.
Preferably: the cost expectation function comprises a shipping spare part dispatching cost expectation function, a loss cost expectation function when the aircraft is out of service and stops at the place, and a shared shipping spare part network spare part storage cost expectation function; wherein,
the shipping equipment piece commissioning cost expectation function is represented by the following formula (4):
Figure GDA0003897739870000141
wherein, a represents the transportation cost of the spare parts of the marine materials at a unit distance; d ic The distance between the ith aviation repair base and the aviation material sharing center library c is represented; p is i (k) Representing the probability of k spare part replacement demands in the ith aviation maintenance base; d is a radical of ij The distance between the ith aviation maintenance base and the jth aviation maintenance base is represented, and i is not equal to j; b = P j (k≤s-1)，P j Representing the probability of needing the spare parts of the aviation materials in the jth aviation maintenance base; d = P Ω (k≤s-1)，P Ω Representing the probability of needing the spare parts of the aviation materials in the aviation maintenance base omega; Ω represents a higher priority base node among all emergency lateral transit points of the ith airline maintenance base than the jth airline maintenance base; { N } represents the set of all emergency lateral terminal nodes for the ith airline maintenance terminal.
The expected loss cost function at the time of the aircraft missing part stopping is represented by the following formula (5):
Figure GDA0003897739870000142
wherein,
Figure GDA0003897739870000143
representing a desired rate of transportation of the turnaround voyage;
the shared aircraft material network spare part storage cost expectation function is represented by the following formula (6):
Figure GDA0003897739870000144
wherein b is the unit storage cost of the turnover member navigation material; s i The stock of the spare parts of the aviation materials of the ith aviation maintenance base.
In the present invention: because the distribution cost of the spare parts of the marine materials consists of the longitudinal distribution cost when the replacement requirement of the marine materials can be met by the stock of the spare parts of the marine materials and the transverse transportation cost when the replacement requirement of the marine materials cannot be met by the stock of the spare parts of the marine materials, the distribution cost expectation function is set as the distribution rule. Because the airplane has an airplane missing part stopping field, the loss cost expectation function is a missing part rule; the storage cost of the spare parts of the aviation materials is formed by the storage cost of all nodes on the aviation materials network, the stock capacity with the delivery rate of an aviation maintenance base i being more than or equal to 98% is used as the maximum stock capacity of the base i, and therefore an expectation function of the storage cost of the spare parts of the shared aviation materials network is established and used as a storage rule.
Preferably: the method comprises the following steps of solving an address selection model of a central library of the marine material spare parts after a cost rule is set based on a particle swarm algorithm, and determining a target address of a central library of the marine material shared, wherein the address selection model comprises the following steps:
step 1: presetting the scale pop of particles, the value range of the particle speed v, the feasible domain range of the particles x, the maximum iteration times maxgen, the inertia weights ws and we and the learning factors c1 and c2;
and 2, step: initializing particle population distribution X = { X1, X2, \8230;, xpop }, and iteration number iter =1;
and 3, step 3: substituting the model into a central base addressing model of the spare parts of the marine products, and updating pbest and gbest; wherein,
pbest represents the optimal position, gbest represents the global historical optimal position;
and 4, step 4: updating the inertia weight w according to the iteration times, and updating the speed v and the position x of each particle according to a speed and position updating formula;
and 5: judging whether the iteration times reach the maximum iteration times maxgen, if so, skipping to the step 6, otherwise, making iter = iter +1 skip to the step 3;
step 6: and outputting the gbest as an optimal addressing point of the addressing model of the central library, and determining a target address of the aviation material sharing central library.
In the present invention: the Particle Swarm Optimization (PSO) algorithm has strong global search capability and high convergence speed. In a central library address selection model of a shared navigation material network, a feasible region of an original problem is a range of a preset region, and a feasible solution is expressed as longitude and latitude coordinates in the range. Assuming a group of "grains" that collectively make up a 3-dimensional space, from longitude, latitude, and shared collaborative cost expectations within a feasible domain, the grains divide the optimal locations (pbest) and global historical optimal locations (gbest) that they have experienced by themselves by the size of the cost expectations. Since the feasible domain range is large in the addressing model of the central library, as can be seen from fig. 4, a large w value and a small slope change slowly at the initial stage of iteration are beneficial to full global search of the particles, and a small w value and a fast slope change with the increase of the iteration times at the later stage of iteration are beneficial to rapid convergence of the particles to the global optimum.
Preferably, the following components: updating the speed v and the position x of each particle according to the speed and position updating formula, wherein the speed v and the position x are represented by the following formula:
Figure GDA0003897739870000161
wherein,
Figure GDA0003897739870000162
representing the velocity of the ith particle at the iter iteration;
Figure GDA0003897739870000163
represents pbest of the ith particle in the iter iteration;
Figure GDA0003897739870000164
represents gbest in the iter iteration;
Figure GDA0003897739870000165
the current position of the ith particle in the iter iteration; w is the inertial weight; c. C 1 And c 2 Is a learning factor; r is 1 And r 2 Are two random numbers which are independent of each other and are uniformly distributed between (0, 1).
Preferably: the updating of the inertia weight w according to the iteration number is represented by the following formula:
Figure GDA0003897739870000166
wherein, w s Representing the maximum value of the inertial weight; w is a e Representing the minimum value of the inertial weight; maxgen represents the total number of iterations; iter denotes the current number of iterations.
The invention also includes a specific embodiment:
aiming at a large revolving part aircraft material of an A320 series model fleet of six airlines, namely A, B, C, D, E and F, a aircraft material resource allocation sharing strategy is implemented, and the site selection work of a shared aircraft material spare part network central library is to be carried out. In order to enhance the overall engineering usability of the model and verify the validity of the model, the preliminary study of the project uses a linear regression method to fit the relationship between the take-off and landing times FS of a fleet of A320 series model of an airline company and the total flying hours FH of the fleet, and then the T is calculated according to the annual take-off and landing times of the fleet of A320 series model of each base FH The fit relationship is shown in fig. 5.
From the fitting results, it was found that R-square was 0.9557 and adj R-square was 0.9459. Therefore, a good second-order linear fitting relationship exists between the two, and the relationship is shown in the following formula:
FH＝-79.13·FS 2 +3120·FS+7.688×10 4
the historical databases of A320 series airplane type fleets of the airlines A to F at each airport are summarized in an aviation quasi-big data website (https:// data. Variflight. Com /) and 2019 from statistics civil aviation, and the taking-off and landing frame times of the airlines A to F at each domestic urban base are screened out and are shown in table 4-1.
TABLE 4-1A 320 series aircraft-type aircraft-team taking-off and landing frame times table for each city base in China
Figure GDA0003897739870000167
Figure GDA0003897739870000171
Figure GDA0003897739870000181
In a shared aviation material network formed by all maintenance bases A-F of an airline company together, calculating the replacement demand rate lambda of spare parts of all the maintenance bases on the network according to a formula (1) i As shown in table 4-2.
TABLE 4-2 request rate λ for replacing aerial materials of partial base station under sharing mode i
Figure GDA0003897739870000191
Further, the supply rate mu of the longitudinal spare parts during longitudinal dispatching from the central warehouse is obtained according to a formula i And a supply rate mu of spare parts supplied from an emergency traverse node j of the station i to the station i during traverse ij . And finally, substituting the change of the address selection area of the central library into a cooperation cost expectation model, and drawing a follow-up central library in MATLABThe collaborative cost expectation for the change of the addressing area is shown in fig. 6.
As can be seen from fig. 6, the light-colored portion represents that the cooperation cost is expected to be high when the position of the center bin c is selected in the area; as the color deepens, the collaborative cost is expected to be lower and lower. It can therefore be concluded that the presence of the optimal addressing point within the feasible region minimizes the cooperation cost expectation, and that the further away the spatial distance from the optimal addressing point, the higher the corresponding cooperation cost expectation. And then, performing iterative optimization on the cooperation cost expectation model according to a 3.2-section particle swarm optimization algorithm flow, wherein an iterative result is shown in the attached figure 7.
FIG. 7 shows that 19 iterations of the algorithm found the lowest cost of cooperation expected to be 1.3114 billion, resulting in geographic location coordinates of the best addressed point of (113 ° 71'15.98 "E, 27 ° 82' 72.61" N). The site selection planning of the aircraft material central repository not only needs to consider the lowest total cooperation cost of multiple airlines, but also needs to ensure that the aircraft material spare parts can be quickly and effectively dispatched to each base node on the shared aircraft material network from the central repository location. Therefore, in order to enable the transportation environment around the central storage to meet the integration of the carrying and distribution conditions of the navigation materials, the optimal site selection point of the central storage with the lowest cooperation cost expectation is considered to be positioned at the adjacent hub airport, so that the purposes of approaching the terminal market and meeting the timeliness and the transportation convenience of transportation of the navigation material spare parts are achieved. As can be seen from fig. 4-2, the lower the position cooperation cost expectation closer to the optimal addressing point, the higher the position cooperation cost expectation farther from the optimal addressing point space, and therefore, the three hub airports closest to the optimal addressing point space are selected as shown in table 4-3.
Table 4-3 shows three hub airports closest to the cost-optimal site selection point in space distance
Figure GDA0003897739870000192
From the perspective of transportation facilities and geographic environmental factors, three positions belong to the locations of hub airports, logistics requirements and transportation convenience required by supply of marine spare parts can be met, and finally, from the perspective of optimization cost, the central warehouse of the turnover marine parts is located in the area near the Changsha yellow international airport and is provided with coordinates of (113 degrees and 23 degrees and 82.45 'E and 28 degrees and 15 degrees and 3.16' N) and the cost is 1.3168 billion. Although the total cost is expected to rise by 54 ten thousand yuan compared with the lowest cooperation cost, in reality, the transportation convenience directly influences the transportation cost and the distribution speed of the material allocation support, and further influences the economic benefit of the material sharing union.
When 6 airlines do not adopt the shared strategy (i.e. non-sharing) of the shipping material resource allocation to the turnover shipping material, the sum of the annual operating costs of the respective operations is 2.6740 billion yuan. FIG. 8 is a graph of the cost of optimization savings for airlines employing the aircraft material resource allocation sharing strategy versus unshared versus the location of a repository site location.
It can be seen that, as the address selection area of the aviation material central library approaches the Changsha yellow flower international airport more and more, the total operating cost is optimized by about 1.3572 yuan by adopting the aviation material resource allocation sharing strategy than that of non-sharing. Obviously, the win-win effect is obvious by adopting an operation mode of sharing the turnover members and the air materials of multiple airlines. Finally, fig. 9 compares the operation states of various indexes of shared and unshared aviation materials.
It can be seen that under the condition that other conditions are consistent and the shipping material payment rate reaches 98%, when the management mode of shipping material resource allocation sharing is adopted, the total stock of the shipping material spare parts required by all the maintenance bases is obviously less than that in a non-sharing state, the size of the spare parts is relatively reduced by 64.46%, and the operation cost is optimized by 50.76%. However, the daily aircraft down time in the fuel sharing mode is higher than in the non-sharing mode. This is because the stock of the headquarters of each airline company is directly supplied with the materials of each maintenance base in the unshared mode, and the headquarters stock is generally located at a central position among all flight-carrying routes, so that the average longitudinal dispatching cycle is short. In addition, in order to ensure that the respective shipping material payment rate reaches more than 98%, each airline company stores part of the shipping material spare parts in respective maintenance bases. However, if the overall situation is viewed, the redundant spare parts will be increased, and if the dimension of the flight materials arranged in the non-cooperative mode is allocated by using the mode of flight material sharing, a higher delivery rate of the flight materials can be ensured in the overall situation, and a larger scale effect can be exerted. Therefore, the method for macroscopically regulating and controlling the spare parts of the aviation materials by using the mode of sharing the aviation material resource allocation has certain practical significance and strategic advantages.
The invention provides a multi-airline company shared aviation material spare part supply strategy based on METRIC theory, conceives an addressing model of a aviation material shared network central library based on an M/M/s/∞/∞ multi-service desk model, and considers three cost factors including shipping material spare part dispatching cost, AOG missing part parking loss cost and spare part storage cost. And then, model verification and simulation analysis are carried out on the examples by combining a particle swarm optimization algorithm, the site selection result is corrected according to traffic facilities around the site selection point and geographic environment factors, and finally the site selection result is compared with the operation result of the airline company in a non-sharing state so as to verify the effectiveness of the strategy and the model. The method developed by the project can provide a theoretical basis for making effective decisions for the address selection work of the aviation material sharing cooperation and the centralized arrangement of the aviation material central library among the airlines.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.

Claims (9)

1. A method for selecting addresses of a aviation material sharing central library based on METRIC is characterized by comprising the following steps:
determining a supply strategy of an aviation maintenance base in an addressing area based on multi-level inventory management, and establishing an addressing model of a central library of aviation spare parts based on queuing operation;
setting a cost rule of the address selection model of the central repository of the marine spare parts based on the expected operation cost;
solving an address selection model of the central library of the marine material spare parts after the cost rule is set based on a particle swarm algorithm, and determining a target address of the central library of the marine material shared;
the method for determining the supply strategy of the aviation maintenance base in the addressing area based on the multilevel inventory management and establishing the addressing model of the central library of the aviation spare parts based on queuing operation comprises the following steps:
determining a dispatching strategy from a shipping material sharing center to an aviation maintenance base in the selected area according to the multi-level inventory management and the optimal ordering batch mode; wherein,
the optimal ordering batch mode is used for determining the optimal ordering quantity from the aircraft material sharing center to the aircraft maintenance base;
the commissioning strategy comprises: a longitudinal transfer strategy and a transverse transfer strategy;
the longitudinal allocation strategy is used for allocating and transporting the aviation material spare parts to the aviation maintenance base to be supplemented through the aviation material sharing center;
the transverse transfer strategy is to transfer the aviation material spare parts to be transferred through the aviation maintenance base to be transferred corresponding to the minimum transfer time;
constructing a model for the aviation material replacement operation and spare part allocation and transportation according to the longitudinal allocation and transportation strategy, the transverse transportation strategy and a preset queue type FCFS service rule;
and determining a supply strategy of the aviation maintenance base in the address selection area according to the model of the aviation material replacement operation and spare part allocation and transportation.
2. The method as claimed in claim 1, wherein the optimal order lot is determined from the material sharing center to the airline maintenance base by the following formula (1):
Figure FDA0003809647460000011
wherein Q is the optimal order quantity; omega i Annual demand for marine material spare parts for the ith airline maintenance base; m is a unit of i Unit transportation cost for longitudinally transporting the aeronautical materials to the ith aviation maintenance base for the shared center of the aeronautical materials; storage c Is a year of unit spare parts for shipping materialsThe keeping cost; i =1,2,3, \8230; \ 8230n; n represents the total number of airline maintenance bases.
3. The method as claimed in claim 1, wherein the building of model for changing and dispatching aviation materials and spare parts according to the longitudinal dispatching strategy, the transverse dispatching strategy and the predetermined queue-type FCFS service rules further comprises:
according to the queue type FCFS service rule, the airplanes needing to be subjected to aircraft spare part replacement in the aircraft maintenance base are subjected to queue ordering according to the time sequence;
determining the longitudinal dispatching time of the spare parts of the aviation materials according to the queue sequencing;
judging whether the queue length is larger than the total stock number of the spare parts of the aviation materials or not according to the longitudinal dispatching time; wherein,
when the queue length is larger than the total stock number of the aviation material spare parts, the requirement of the aviation maintenance base cannot be met by the stock of the aviation maintenance base, the transverse transfer strategy is started emergently to supplement the aviation material spare parts for the aviation maintenance base,
when the queue length is less than or equal to the total inventory number of the aviation spare parts, the requirement of the aviation maintenance base can be met by the inventory of the aviation maintenance base, and a longitudinal dispatching strategy is executed.
4. The method of claim 1, wherein the lateral diversion strategy further comprises:
determining priority sequencing of emergency transverse transfer of different aviation maintenance bases according to the transfer time; wherein,
the priority ranking is determined by the replacement demand rate of spare parts and the transverse transfer supply rate of the aviation maintenance base to be supplemented;
the spare part replacement demand rate obeys poisson distribution, and is determined by the following formula (2):
Figure FDA0003809647460000021
wherein λ is ri Representing the actual replacement demand rate of the spare parts of the aircraft materials of the ith aviation maintenance base in the sharing mode, and r representing the actual value in the sharing mode; lambda [ alpha ] i Representing the replacement demand rate of the aviation material spare parts of the ith aviation maintenance base in the unshared mode; { I } represents a node set with the ith airline maintenance base as an emergency lateral transit point; theta represents a base node which takes the ith aviation maintenance base as an emergency transverse transit point; p is θ Representing the probability of needing the spare parts of the navigation materials in the theta node; k represents the queue length of the spare parts of the aviation materials needing to be replaced; s represents the total stock quantity of the spare parts of the aviation materials; lambda θ Representing the replacement demand rate of the spare parts of the navigation materials of the theta nodes in the non-sharing mode; epsilon represents a base node with higher priority than the repair base i among all the emergency lateral transit points of the theta aviation repair base; { H } represents a set of base nodes with higher priority than i among all the urgent lateral transit points of the θ node; p ε Representing the probability of needing the spare parts of the aviation materials in the aviation maintenance base epsilon;
the lateral transfer supply rate is a desired value of the actual aircraft material spare part supply capacity of the aviation maintenance base to be supplemented, and is represented by the following formula (3):
Figure FDA0003809647460000031
wherein, A = P i (k≤s-1)；P i Representing the probability that the ith aviation maintenance base needs the spare parts of the aviation materials; mu.s i Representing the supply capacity expectation of the ith aviation maintenance base; τ denotes an emergency lateral transfer point of the ith airline maintenance base; { V } represents the set of emergency lateral transfer points for the ith airline maintenance base; σ represents an advanced base node with higher priority than τ among all emergency lateral transit points of the ith airline maintenance base; { Z } represents the set of base nodes with higher priority than τ among all the emergency lateral transit points of the ith airline maintenance base; p is σ Representing the probability of needing the spare parts of the marine materials in the sigma-th advanced base node; p τ Representing the probability of needing spare parts of the navigation materials in the emergency transverse transit point tau; mu.s iτ Indicating the supply capacity expectation of the emergency lateral transfer point tau for the aircraft material spare parts of the ith airline maintenance base.
5. The method of claim 1, wherein the setting of the cost rule of the model of locating the marine material spare part repository based on the operational cost expectation comprises:
obtaining the operation cost expectation, and determining a cost expectation composition; wherein,
the cost expectation components include: the method comprises the following steps of expecting the dispatching cost of spare parts of the aviation materials, expecting the loss cost when the aircraft is in a missing part stop place and expecting the storage cost of spare parts of a shared aviation material network;
determining a cost expectation value according to the cost expectation composition;
setting a cost expectation function of the address selection model of the central library of the spare parts of the aviation materials according to the cost expectation value;
and constructing a cost rule based on cost expectation according to the cost expectation function.
6. The method as claimed in claim 5, wherein the cost expectation function includes a shipping material spare part distribution cost expectation function, a loss cost expectation function when the aircraft is in a missing part parking lot, and a shared shipping material network spare part storage cost expectation function; wherein,
the shipping equipment piece commissioning cost expectation function is represented by the following formula (4):
Figure FDA0003809647460000041
wherein a represents the transportation cost of the spare parts of the marine materials at a unit distance; d ic Representing the distance between the ith aviation maintenance base and the aviation materials sharing center library c; p is i (k) Representing the probability of k spare part replacement demands in the ith aviation maintenance base; d ij The distance between the ith aviation maintenance base and the jth aviation maintenance base is represented, and i is not equal to j; b = P j (k≤s-1)，P j Representing the probability of needing the spare parts of the aviation materials in the jth aviation maintenance base; d = P Ω (k≤s-1)，P Ω Representing the probability of needing the spare parts of the aviation materials in the aviation maintenance base omega; Ω represents a higher priority base node than the jth airline maintenance base among all emergency lateral transit points of the ith airline maintenance base; { N } represents the set of base nodes with higher priority than j among all the emergency transverse transit base nodes of the ith airline maintenance base;
n represents the total number of airline maintenance bases; k represents the queue length of the spare parts of the aviation materials needing to be replaced; s represents the total stock quantity of the spare parts of the aviation materials; a = P i (k is less than or equal to s-1) and represents the probability of needing the spare parts of the aviation materials in the ith aviation maintenance base; { J } represents the set of emergency lateral transit base nodes for the ith airline maintenance base;
the expected loss cost function at the time of the aircraft missing part stopping is represented by the following formula (5):
Figure FDA0003809647460000042
wherein,
Figure FDA0003809647460000043
representing a desired rate of transportation of the turnaround voyage;
the shared aircraft material network spare part storage cost expectation function is represented by the following formula (6):
Figure FDA0003809647460000044
wherein b is the unit storage cost of the turnover member navigation material; s is i The stock of the spare parts of the aviation materials of the ith aviation maintenance base.
7. The method for locating the marine material shared central library based on the METRIC as claimed in claim 1, wherein the method for locating the marine material shared central library based on the particle swarm optimization solves the model for locating the marine material spare central library after the cost rule is set, and the target address of the marine material shared central library is determined, comprising the following steps:
step 1: presetting the scale pop of particles, the value range of the particle velocity v, the feasible domain range of the particle position x, the maximum iteration times maxgen, the maximum value ws of the inertia weight, the minimum value we of the inertia weight and learning factors c1 and c2;
step 2: initializing particle population distribution X = { X1, X2, \8230;, xpop }, and iteration times iter =1;
and step 3: substituting the model into a central base addressing model of the spare parts of the marine products, and updating pbest and gbest; wherein,
pbest represents the optimal position, gbest represents the global historical optimal position;
and 4, step 4: updating the inertia weight w according to the iteration times, and updating the speed v and the position x of each particle according to a speed and position updating formula;
and 5: judging whether the iteration times reach the maximum iteration times maxgen, if so, skipping to the step 6, otherwise, making iter = iter +1 skip to the step 3;
and 6: and outputting the gbest as an optimal addressing point of the addressing model of the central library, and determining a target address of the aviation material sharing central library.
8. The method as claimed in claim 7, wherein the velocity v and the position x of each particle are updated according to a velocity and position updating formula, and are expressed by the following formula:
Figure FDA0003809647460000051
wherein,
Figure FDA0003809647460000052
represents the speed of the ith particle at the ith iterationDegree;
Figure FDA0003809647460000053
represents pbest of the ith particle in the iter iteration;
Figure FDA0003809647460000054
representing gbest in the iter iteration;
Figure FDA0003809647460000055
the current position of the ith particle in the iter iteration; w is the inertial weight; c. C 1 And c 2 Is a learning factor; r is a radical of hydrogen 1 And r 2 Are two random numbers which are independent of each other and are uniformly distributed between (0, 1).
9. The method as claimed in claim 7, wherein the updating of the inertia weight w according to the number of iterations is represented by the following equation:
Figure FDA0003809647460000056
wherein w s Representing the maximum value of the inertial weight; w is a e Representing the minimum value of the inertial weight; maxgen represents the total number of iterations; iter denotes the current number of iterations.
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