CN107977740A - A kind of scene O＆M intelligent dispatching method - Google Patents
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Abstract
The invention discloses a kind of live O＆M intelligent dispatching method to include：Corresponding mathematical model is established to multiple targets of live O＆M respectively, wherein, the target of live O＆M includes that task completion time is most short, task completes that quality highest, resource utilization highest, queuing time are most short and load is most balanced；Task, personnel and resource in collection site O＆M；According to task, personnel and the resource in the live O＆M, multiple populations are generated at random；Each task, personnel and resource in the population is numbered, and generates multiple initial chromosome codings；Encoded according to default improved adaptive GA-IAGA and the multiple initial chromosome, the corresponding mathematical model of the multiple target is solved, draw scheduling scheme of the optimal solution as live O＆M.This method can realize the multiple-objection optimization of on-site maintenance, and the algorithmic procedure of objective optimization is simple, improve the efficiency of on-site maintenance.
Description
Technical field
The present invention relates to intelligent scheduling field, and in particular to a kind of scene O＆M intelligent dispatching method.
Background technology
The fast-developing of powerline network requires that its operation management level and benefit is continuously improved, to electric communication operation and maintenance
Management proposes more strict requirements.Live O＆M be electric communication operation and maintenance work important component, the peace of its work
Entirely, quality and efficiency are directly related to the effect of electric communication operation and maintenance work.At present, live O＆M is typically all to pass through personnel's skill
The custom of art, the experience of accumulation or long-term accumulation operates equipment, often produces habitual violating the regulations or violation safety
The behavior of operating provision；Lack effective practical intelligent supporting method at the same time to help live operation maintenance personnel lifting O＆M energy
Power, causes that live O＆M inefficiency, work order utilization rate are low, O＆M quality is low.Influence the target factor master of live O＆M level
To include the speed of performing task, tasks carrying quality, overall queuing time, load balancing, resource utilization etc., these factors it
Between influence each other, interaction.
But in the prior art, operation only usually is optimized on one of them in live O＆M influence target factor,
Such as：A kind of work planing method of live O＆M day (CN106934484A) based on PDA describes first, obtains abnormal point and gathers
Symphysis exception work order and according to sending work area domain Exception Filter work order；Second, the maintenace point of abnormal work order is calculated to stationary point shortest path
Footpath and mutual shortest path simultaneously generate duplicate paths matrix；3rd, preliminary route chained list is generated by scanning duplicate paths matrix,
Acquisition tentatively sends work route, and presses urgency descending sort；4th, the preliminary route of maximum urgency is chosen, and it is carried out
Add some points or delete a judgement；5th, an algorithm is added some points or deleted in execution, and generation finely sends work route so that each sends work route work
As amount, that is, saturation again without departing from regulation workload, and the total urgency of route is high；This method, which is realized, accurately sends work algorithm, O＆M resource
Waste small, but entirely send work algorithmic procedure more complicated, and work the speed performed and quality can not be guaranteed, from entirety
From the point of view of cannot improve the efficiency of on-site maintenance well.
The content of the invention
The object of the present invention is to provide a kind of live O＆M intelligent dispatching method, it can realize that the multiple target of on-site maintenance is excellent
Change, the algorithmic procedure of objective optimization is simple, improves the efficiency of on-site maintenance.
To solve above technical problem, the embodiment of the present invention provides a kind of live O＆M intelligent dispatching method, including：
Corresponding mathematical model is established to multiple targets of live O＆M respectively, wherein, the target of live O＆M includes appointing
Being engaged in, the deadline is most short, task completes that quality highest, resource utilization highest, queuing time are most short and load is most balanced；
Task, personnel and resource in collection site O＆M；
According to task, personnel and the resource in the live O＆M, multiple populations are generated at random；
Each task, personnel and resource in the population is numbered, and generates multiple initial chromosomes and compiles
Code；
Encoded according to default improved adaptive GA-IAGA and the multiple initial chromosome, it is corresponding to the multiple target
Mathematical model is solved, and draws scheduling scheme of the optimal solution as live O＆M.
Preferably, the default improved adaptive GA-IAGA includes：
Non-dominated ranking operation is carried out to multiple initial chromosomes coding of the population, and according to the initial chromosome
The partial ordering relation of coding selects initial chromosome to be intersected to encode；
Crossover operation, generation Cross reaction body coding are carried out to initial chromosome coding to be intersected described in any two；
The Cross reaction body is encoded and carries out mutation operation, generation child chromosome coding；
Iterations adds one, and judges whether the child chromosome coding reaches the default condition of convergence；
When child chromosome coding is not up to the default condition of convergence, by child chromosome coding more
Newly into the population, non-dominated ranking, intersection and mutation operation are repeated to the population after renewal；
When the child chromosome is encoded up the default condition of convergence, the child chromosome coding is calculated
The middle optimal solution for solving the corresponding mathematical model of the multiple target, draws dispatching party of the optimal solution as live O＆M
Case.
Preferably, task, personnel and the resource in the live O＆M, generates multiple populations, has at random
Body includes：
Judge whether the personnel meet personnel's constraints, and the personnel for meeting personnel's constraints are defined as
Effective personnel；
Judge whether the task meets resource constraint, and will meet the definition of the task of the resource constraint
For effective task；
According to the effectively task, effectively personnel and the resource, multiple populations are generated at random；
Preferably, personnel's constraints is in idle condition including the personnel and performs y roads in the task
The technical ability coefficient of the personnel of process is higher than the minimum requirements of the y procedures；The resource constraint includes the task
Occupancy resource be not more than the resource.
Preferably, multiple initial chromosomes coding to the population carries out non-dominated ranking operation, and according to institute
The partial ordering relation for stating initial chromosome coding selects initial chromosome to be intersected to encode, and specifically includes：
The population is traveled through, multiple boundary sets are generated according to non-dominated ranking rule；
The crowding distance encoded according to the multiple boundary set and the initial chromosome, to the initial dye in the population
Colour solid coding is ranked up；
Initial chromosome to be intersected is selected to encode according to the partial ordering relation that the initial chromosome after sequence encodes.
The partial ordering relation that the initial chromosome according to after sequence encodes selects initial chromosome to be intersected to compile
Code, specifically includes：
Preferably, the partial ordering relation that the initial chromosome according to after sequence encodes selects initial dye to be intersected
Colour solid encodes, and specifically includes：
When i-th initial chromosome coding is with j-th initial chromosome coding when meeting default partial order condition, selection
I-th of initial chromosome coding is encoded with j-th of initial chromosome coding as initial chromosome to be intersected；Wherein, it is described
Default partial order condition is：Belong to different sides and if only if i-th of initial chromosome coding and j-th of initial chromosome coding
When boundary collects, no more than j-th initial chromosome coding of sequence number that i-th of initial chromosome encodes corresponding boundary set is corresponding
The sequence number of boundary set, and the crowding distance of i-th initial chromosome coding be more than the aggregation of j-th of initial chromosome coding away from
From.
Preferably, the live O＆M intelligent dispatching method includes:
Encoded according to the initial chromosome of adjacent two is encoded with i-th of initial chromosome in each mesh
The range difference put on, calculates the crowding distance of i-th of initial chromosome coding.
Preferably, the live O＆M intelligent dispatching method includes:
According to formulaCalculate i-th of initial chromosome coding
Crowding distance di；
Wherein, di+1*fmIt is that the i+1 initial chromosome is encoded in m-th of sub-goal fmOn functional value, di-1*fm
It is that the i-th -1 initial chromosome is encoded in m-th of sub-goal fmOn functional value.
Preferably, described to carry out crossover operation to initial chromosome coding to be intersected described in any two, generation intersects
Chromosome coding, specifically includes：
A hybridization point is randomly generated, the hybridization point will be located in initial chromosome coding to be mingled described in two
Code segment afterwards exchanges, and generates the Cross reaction body coding.
Preferably, described encoded to the Cross reaction body carries out mutation operation, generation child chromosome coding, specific bag
Include：
A variable position is randomly generated, the person number of the variable position is corresponded to during the Cross reaction body is encoded
Or another person number or resource number of resource number random replacement for same type, generate the child chromosome coding.
Relative to the prior art, the embodiment of the present invention provides a kind of beneficial effect of live O＆M intelligent dispatching method and exists
In：The scene O＆M intelligent dispatching method includes：Corresponding mathematical model is established to multiple targets of live O＆M respectively, its
In, when the target of live O＆M includes most short task completion time, task completion quality highest, resource utilization highest, queuing
Between it is most short and load it is most balanced；Task, personnel and resource in collection site O＆M；Appointing in the live O＆M
Business, personnel and resource, generate multiple populations at random；Each task, personnel and resource in the population is compiled
Number, and generate multiple initial chromosome codings；Encoded according to default improved adaptive GA-IAGA and the multiple initial chromosome,
The corresponding mathematical model of the multiple target is solved, draws scheduling scheme of the optimal solution as live O＆M.This method
It can realize the multiple-objection optimization of on-site maintenance, the algorithmic procedure of objective optimization is simple, improves the efficiency of on-site maintenance.
Brief description of the drawings
Fig. 1 is a kind of flow chart of live O＆M intelligent dispatching method provided in an embodiment of the present invention；
Fig. 2 is the flow chart of improved adaptive GA-IAGA default in Fig. 1；
Fig. 3 is to use method and the comparison diagram of the task completion time of manual dispatching method in Fig. 1；
Fig. 4 is the comparison diagram for using method and the task completion quality of manual dispatching method in Fig. 1；
Fig. 5 is the comparison diagram for using method and the resource utilization of manual dispatching method in Fig. 1；
Fig. 6 is to use method and the comparison diagram of the queuing time of manual dispatching method in Fig. 1；
Fig. 7 is the comparison diagram for using method and the load balancing of manual dispatching method in Fig. 1.
Embodiment
Below in conjunction with the attached drawing in the embodiment of the present invention, the technical solution in the embodiment of the present invention is carried out clear, complete
Site preparation describes, it is clear that described embodiment is only part of the embodiment of the present invention, instead of all the embodiments.It is based on
Embodiment in the present invention, those of ordinary skill in the art are obtained every other without creative efforts
Embodiment, belongs to the scope of protection of the invention.
Referring to Fig. 1, a kind of flow chart of its live O＆M intelligent dispatching method that to be one embodiment of the invention provided,
The scene O＆M intelligent dispatching method includes：
S1：Corresponding mathematical model is established to multiple targets of live O＆M respectively, wherein, the target of live O＆M includes
Task completion time is most short, task completes that quality highest, resource utilization highest, queuing time are most short and load is most balanced；
S2：Task, personnel and resource in collection site O＆M；
S3：According to task, personnel and the resource in the live O＆M, multiple populations are generated at random；
In the present embodiment, with reference to the actual conditions of live O＆M, according to the geographical location of the task, acquisition is located at institute
The personnel in the geographical location setting range of business and resource are stated, generates the initial population.According to the geography of the business
Position generates initial population, advantageously reduces scheduling cost, shortens the time that task is completed.For example, obtain any task periphery
Available personnel, then therefrom select the task quantity of burden less than pre-set task quantity critical value h and possess
The personnel assignment of task negligible amounts gives the task so that the task quantity of each personnel's burden is as far as possible average, is conducive to carry
The completion quality of high task and the utilization rate of resource.
S4：Each task, personnel and resource in the population is numbered, and generates multiple initial chromosomes
Coding；
The present embodiment is using the Indirect encod mode of task based access control-resource, each task, personnel and resource
It is numbered in advance, an original chromosome coding is generated according to a series of numbering of business, personnel and resource.Example
Such as：QmRepresent the m articles original chromosome coding, P in the populationmi、Cmi、OmiIt is the base in the m articles original chromosome coding
Cause, wherein, PmiRepresent the personnel of i-th of task distribution, CmiRepresent the vehicle that i-th of task uses, OmiRepresent i-th of task
The instrument used, then QmIt can be expressed as：
Qm=Pm1, Cm1, Om1, Pm2, Cm2, Om2... ..., Pmn, Cmn, Omn}(1)
When setting the quantity k of the personnel as 3, corresponding set P=P1, P2, P3, the quantity of the vehicle is 3, corresponding
Set C=C1, C2, C3, the quantity of the instrument is 3, corresponding set O=O1, O2, O3, the quantity n of the task is 5, right
The collection answered is combined into R=R1, R2, R3, R4, R5, wherein, the length l=3n of chromosome.Each genic value on the chromosome
Corresponding personnel, the numbering of resource are represented, a variety of allocative decisions can be determined using random manner, such as：
(1)P1:1,5；P2：2,4；P3:3；C1:1,4；C2：3,5；C3：2；O1：2,5；O2：1；O3：3,4；
(2)P1:2；P2：3,5；P3:1,4；C1:2,5；C2：3；C3：1,4；O1：1,5；O2：2,4；O3：3；
It is respectively for the corresponding original chromosome coding of above-mentioned allocative decision：
(1)Q1={ 112 231 323 213 121 }
(2)Q2={ 331 112 223 332 211 }
Wherein, { 112 231 323 213 121 } represent task 1 by personnel P1Use vehicle C1With instrument O2Complete, task
2 by personnel P2Use vehicle C3With instrument O1Complete, task 3 is by personnel P3Use vehicle C2With instrument O3Complete, task 4 is by personnel
P2Use vehicle C1With instrument O3Complete, task 5 is by personnel P1Use vehicle C2With instrument O1Complete.
If the quantity such as task, personnel, vehicle, instrument more than 9, are represented, with such using two in gene
Push away.
S5：Encoded according to default improved adaptive GA-IAGA and the multiple initial chromosome, to the multiple target pair
The mathematical model answered is solved, and draws scheduling scheme of the optimal solution as live O＆M.
The scene O＆M intelligent dispatching method can be tried to achieve effectively under various conditions (task, personnel and resource)
Scheduling scheme, by rational dispatcher, can realize faster execution speed, higher execution quality, shorter queuing
Time, higher resource utilization, more balanced load.The scene O＆M intelligent dispatching method passes through to be optimized to dispatching
Multiple targets carry out mathematical modeling, and the solution of mathematical model is carried out based on the default genetic algorithm, draws optimal solution
For scheduling scheme, the time complexity of calculating is reduced, there is stronger ability of searching optimum and flexibility ratio, while can realized existing
The multiple-objection optimization that field is safeguarded, the algorithmic procedure of objective optimization is simple, improves the efficiency of on-site maintenance.
In a kind of optional embodiment, referring to Fig. 2, it is the flow chart of improved adaptive GA-IAGA default in Fig. 1,
The default improved adaptive GA-IAGA includes：
S51：Non-dominated ranking operation is carried out to multiple initial chromosomes coding of the population, and according to the initial dye
The partial ordering relation of colour solid coding selects initial chromosome to be intersected to encode；
S52：Crossover operation is carried out to initial chromosome coding to be intersected described in any two, generation Cross reaction body is compiled
Code；
S53：The Cross reaction body is encoded and carries out mutation operation, generation child chromosome coding；
S54：Iterations adds one, and judges whether the child chromosome coding reaches the default condition of convergence；
S55：When child chromosome coding is not up to the default condition of convergence, the child chromosome is compiled
Code renewal repeats non-dominated ranking, intersection and mutation operation into the population, to the population after renewal；
S56：When the child chromosome is encoded up the default condition of convergence, the child chromosome is calculated
The optimal solution of the corresponding mathematical model of the multiple target is solved in coding, draws scheduling of the optimal solution as live O＆M
Scheme.
In a kind of optional embodiment, the scene O＆M intelligent dispatching method includes：
The default condition of convergence is encoded to the corresponding mathematical model of the multiple target for continuous N for child chromosome
The change of drawn target solution value is solved in the range of setting.
The scope of the setting more tends to zero, and the child chromosome coding convergence effect is better, and the optimal solution drawn is most
It is good, most there is scheduling scheme so as to draw live O＆M.
In a kind of optional embodiment, S3：It is random raw according to task, personnel and the resource in the live O＆M
Into multiple populations, specifically include：
Judge whether the personnel meet personnel's constraints, and the personnel for meeting personnel's constraints are defined as
Effective personnel；
Judge whether the task meets resource constraint, and will meet the definition of the task of the resource constraint
For effective task；
According to the effectively task, effectively personnel and the resource, multiple populations are generated at random.
Wherein, personnel's constraints is in idle condition including the personnel and performs y roads work in the task
The technical ability coefficient of the personnel of sequence is higher than the minimum requirements of the y procedures；The resource constraint includes the task
Take resource and be not more than the resource.
Factor needed to be considered has personnel, resource and task three major types in the scheduling process that whole scene is safeguarded.Everyone
Member has respective attribute, including ability information, positional information and status information.Ability information represents which kind of operation maintenance personnel possesses
Ability (tour, maintenance, failed operation, service fulfillment etc.) and corresponding ability rating, ability rating is by project team director
Give and evaluate；Positional information shows personnel present position；Status information is divided into busy and two kinds idle.Resource includes the kind of resource
Class and quantity.Task include flow of task, it is necessary to technical ability and instrument.
In the present embodiment, since the personnel at O＆M scene and resource are limited, all tasks can not be usually met at the same time
It is required that therefore scheduling must be fulfilled for personnel's constraints and resource constraint, i.e., described task RxOccupancy resource be not more than
The resource (i.e. total number resource)；Personnel PiNeed at the same time to meet in idle condition and perform y procedures in the task
Personnel technical ability coefficient be higher than the y procedures minimum requirements when, personnel PiIt can just be allocated and perform the task
In y procedures.
Such as：The function representation that personnel are in idle condition is：Sxy=1, (2)
Wherein, there are (0 ＜ y≤q to any x (0 ＜ x≤n)x), n represents task quantity, qxRepresent task RxProcess
Number, SxyRepresent completion task RxY procedures personnel state, O represents busy, and 1 represents the free time.
Execution task RxIn y procedures personnel technical ability coefficient higher than the y procedures minimum requirements letter
Number is expressed as：
Wherein there are (0 ＜ y≤q to any x (0 ＜ x≤n)x), lxyRepresent task RxY procedures needed for technical ability；Task R is distributed in representativexY procedures personnel technical ability.
The task RxOccupancy resource be no more than the function representation of the resource：
Wherein, there are (0 ＜ y≤q to any x (0 ＜ x≤n)x), OxyRepresent completion task RxY procedures needed for
Resource collection.
Only to meeting that above-mentioned function (2), (3), the task of (4), the personnel and the resource carry out population and draw
Point, scheduling cost can be advantageously reduced, shortens the time that task is completed so that the task quantity of each personnel's burden is as far as possible flat
, the completion quality of raising task and the utilization rate of resource are conducive to.
Wherein, the target of live O＆M：Complete most short task time, O＆M quality highest, resource utilization highest, queuing
Time is most short, the most balanced corresponding mathematical model expression of load is as follows：
(1) it is most short to complete task time：
Wherein, txRepresent task RxDeadline.
(2) O＆M quality highest：
(3) resource utilization highest：
(4) queuing time is most short：
Wherein, TxRepresent RxyStand-by period.
(5) load most balanced：Wherein
Wherein, FiRepresent personnel PiThe task amount of completion, k represent the quantity of personnel.
In a kind of optional embodiment, S51：Non-dominated ranking is carried out to multiple initial chromosomes coding of the population
Operation, and select initial chromosome to be intersected to encode according to the partial ordering relation that the initial chromosome encodes, specifically include：
The population is traveled through, multiple boundary sets are generated according to non-dominated ranking rule；
The crowding distance encoded according to the multiple boundary set and the initial chromosome, to the initial dye in the population
Colour solid coding is ranked up；
Initial chromosome to be intersected is selected to encode according to the partial ordering relation that the initial chromosome after sequence encodes.
In the present embodiment, it is possible to understand that the corresponding individual of initial chromosome coding, i.e., described population G bags
Containing multiple individuals.The non-dominated ranking constitution step of the multiple boundary set is as follows：
(1) the population G is traveled through, each individual is obtained and dominates group of individuals；
(2) quantity for being dominated individual of each individual is calculated；
(3) result that is obtained according to step (2) divides each boundary set；
Wherein, the first boundary set is not belonged to by the individual that any individual dominates, to individual described in first boundary set
Domination group of individuals repeat the above steps (1), (2), (3), obtain not dominated in the set by any individual
Body is the second boundary collection, and so on, group of individuals's (set of i.e. described original chromosome coding) of population is carried out non-
Dominated Sorting.
In a kind of optional embodiment, the partial ordering relation that the initial chromosome according to after sequence encodes selects
Initial chromosome coding to be intersected, specifically includes：
When i-th initial chromosome coding is with j-th initial chromosome coding when meeting default partial order condition, selection
I-th of initial chromosome coding is encoded with j-th of initial chromosome coding as initial chromosome to be intersected；；Wherein, it is described
Default partial order condition (i >=nJ) it is：Belong to and if only if i-th of initial chromosome coding and j-th of initial chromosome coding
During different boundary set, no more than j-th initial chromosome of sequence number that i-th of initial chromosome encodes corresponding boundary set encodes
The sequence number of corresponding boundary set, and the crowding distance of i-th of initial chromosome coding is more than what j-th of initial chromosome encoded
Crowding distance.
It is sorted when the original chromosome coding is based on boundary set and crowding distance, then original chromosome to be intersected
The selection operation of coding is carried out without using the size of adaptive value but using partial ordering relation.
In a kind of optional embodiment, the scene O＆M intelligent dispatching method includes:
Encoded according to the initial chromosome of adjacent two is encoded with i-th of initial chromosome in each mesh
The range difference put on, calculates the crowding distance of i-th of initial chromosome coding.
When producing new colony, while usually will be outstanding the smaller individual of gather density retain and participate in it is of future generation into
Change.Its small individual crowding distance of gather density is big on the contrary, and therefore, the crowding distance of an individual can be by calculating and its phase
The sum of the range difference of two adjacent individuals in each target is asked for.
In a kind of optional embodiment, the scene O＆M intelligent dispatching method includes:
According to formula (10)Calculate j-th of initial chromosome
The crowding distance d of codingj；
Wherein, dj+1*fmIt is that the initial chromosome of jth+1 is encoded in m-th of target fmOn functional value, dj-1*fmFor
The initial chromosome coding of jth -1 is in m-th of target fmOn functional value.
For convenience of data manipulation, to the crowding distance d according to the following formulajIt is standardized operation：
Wherein,Represent individual in m-th of object function f respectivelymOn maximum and minimum value.
In a kind of optional embodiment, S52：Initial chromosome coding to be intersected described in any two is intersected
Operation, generation Cross reaction body coding, specifically includes：
A hybridization point is randomly generated, the hybridization point will be located in initial chromosome coding to be mingled described in two
Code segment afterwards exchanges, and generates the Cross reaction body coding.
Such as：For following two original chromosome coding Q1={ 112 231 323 213 121 } and Q2={ 331 112
223 332 211 }, a hybridization point 6 is randomly generated, then to Q1And Q2Genic value behind 6th gene location swaps,
So as to produce two Cross reaction body coding Q '1={ 112 231 223 332 211 } and Q '2={ 331 112 323 213
121}。
In a kind of optional embodiment, the scene O＆M intelligent dispatching method includes：
According to formula (12)Calculate described intersect generally
Rate Pc；
Wherein, the Pc1And Pc2It is constant, and 0 ＜ Pc2＜ Pc1＜ 1, F ' are that two of participation crossover operation are described initial
Higher fitness, F in chromosome codingmaxRepresent fitness maximum in the population, FavgRepresent being averaged for the population
Fitness.
Adaptive mode is taken in the present embodiment for the crossover probability, avoids crossover probability from crossing havoc fitness
The structure of higher original chromosome coding, while avoid the too small search efficiency for reducing algorithm of crossover probability.
In a kind of optional embodiment, S53：The Cross reaction body is encoded and carries out mutation operation, generation filial generation dye
Colour solid encodes, and specifically includes：
A variable position is randomly generated, the person number of the variable position is corresponded to during the Cross reaction body is encoded
Or another person number or resource number of resource number random replacement for same type, generate the child chromosome coding.
Such as：Q ' is encoded to Cross reaction body1={ 112 231 223 332 211 }, randomly generate a variable position
4, then Cross reaction body is encoded into Q1In the 4th genic value be replaced, when the 4th genic value represents the numbering of personnel,
4th genic value is replaced with to the numbering of the less personnel of distribution task；When the 4th genic value represents the numbering of resource
When, the 4th genic value is replaced with to the numberings of same type other resources randomly selected；Obtain son after variation
It is Q " for chromosome coding1={ 112 131 223 332 211 }.
In a kind of optional embodiment, the scene O＆M intelligent dispatching method includes：
According to formula (13)Calculate described intersect generally
Rate Pm；
Wherein, the Pm1And Pm2It is constant, and 0 ＜ Pm2＜ Pm1 ＜ 1, F are the Cross reactions for participating in mutation operation
The fitness of body coding, FmaxRepresent fitness maximum in the population, FavgRepresent the average fitness of the population.
Mutation operation is the further evolutionary process on the basis of crossover operation, similar to produce new chromosome coding
In gene mutation process.Therefore, mutation operation is random selection chromosome and gene position, is allowed to produce the process of mutation.Variation
On the one hand the random searching ability of algorithm can be strengthened, on the other hand can also accelerate algorithm to the convergent speed of optimal solution.
Below can only dispatching method illustration to the live O＆M：The quantity of required by task resource is arranged to：People
Member 10,5, vehicle, number of tools 10, task quantity changes to 100 from 20.Major parameter in Revised genetic algorithum
It is arranged to:Population scale is 90, wherein Pc1=0.8, Pc2=0.3, Pm1=0.05, Pm2=0.01, crossover probability PcIt is general with variation
Rate PmAccording to formula (12) and formula (13) with search procedure dynamic change.When the iterations of Revised genetic algorithum reaches
During maximum evolutionary generation MaxAge (MaxAge is arranged to 300), Revised genetic algorithum is terminated, but if iteration expires every time
300, calculation amount is very big, is found by analyzing and testing when five mesh target values of continuous multi-generation (k) change all little, can
To determine that algorithm has been restrained, at this time can also termination algorithm (value of k is set to 100 by analyzing, at this time both can not be so as not to
To local convergence as a result, can also shorten the execution time of algorithm at the same time), so it is substantially shorter execution time of algorithm.Appoint
Deadline, task completion quality, resource utilization, queuing time, the comparing result of load be engaged in as shown in Fig. 3 to Fig. 7.
In from Fig. 3 to Fig. 7 as can be seen that when task amount is smaller, traditional manual scheduling is in task completion time, task
Complete to be better than genetic algorithm in terms of quality, resource utilization, queuing time and load balancing, this is because, when task amount is small
When, problem is relatively simple, and what scheduling can be relatively good by hand solves the problems, such as, but when task amount gradually increases, problem
Complexity sharply increases, and scheduling by hand cannot complete task well, and the performance of genetic algorithm in all fields at this time is better than
Scheduling by hand.
Relative to the prior art, the embodiment of the present invention provides a kind of beneficial effect of live O＆M intelligent dispatching method and exists
In：The scene O＆M intelligent dispatching method includes：Corresponding mathematical model is established to multiple targets of live O＆M respectively, its
In, when the target of live O＆M includes most short task completion time, task completion quality highest, resource utilization highest, queuing
Between it is most short and load it is most balanced；Task, personnel and resource in collection site O＆M；Appointing in the live O＆M
Business, personnel and resource, generate multiple populations at random；Each task, personnel and resource in the population is compiled
Number, and generate multiple initial chromosome codings；Encoded according to default improved adaptive GA-IAGA and the multiple initial chromosome,
The corresponding mathematical model of the multiple target is solved, draws scheduling scheme of the optimal solution as live O＆M.This method
It can realize the multiple-objection optimization of on-site maintenance, the algorithmic procedure of objective optimization is simple, improves the efficiency of on-site maintenance.
Above is the preferred embodiment of the present invention, it is noted that for those skilled in the art,
Various improvements and modifications may be made without departing from the principle of the present invention, these improvements and modifications are also considered as this hair
Bright protection domain.
Claims (10)
- A kind of 1. scene O＆M intelligent dispatching method, it is characterised in that including：Corresponding mathematical model is established to multiple targets of live O＆M respectively, wherein, the target of live O＆M is complete including task Into the time is most short, task completes that quality highest, resource utilization highest, queuing time are most short and load is most balanced；Task, personnel and resource in collection site O＆M；According to task, personnel and the resource in the live O＆M, multiple populations are generated at random；Each task, personnel and resource in the population is numbered, and generates multiple initial chromosome codings；Encoded according to default improved adaptive GA-IAGA and the multiple initial chromosome, mathematics corresponding to the multiple target Model is solved, and draws scheduling scheme of the optimal solution as live O＆M.
- 2. scene O＆M intelligent dispatching method as claimed in claim 1, the default improved adaptive GA-IAGA include：Non-dominated ranking operation is carried out to multiple initial chromosomes coding of the population, and is encoded according to the initial chromosome Partial ordering relation select initial chromosome to be intersected to encode；Crossover operation, generation Cross reaction body coding are carried out to initial chromosome coding to be intersected described in any two；The Cross reaction body is encoded and carries out mutation operation, generation child chromosome coding；Iterations adds one, and judges whether the child chromosome coding reaches the default condition of convergence；When child chromosome coding is not up to the default condition of convergence, child chromosome coding renewal is arrived In the population, non-dominated ranking, intersection and mutation operation are repeated to the population after renewal；When the child chromosome is encoded up the default condition of convergence, calculates and solved in the child chromosome coding The optimal solution of the corresponding mathematical model of certainly the multiple target, draws scheduling scheme of the optimal solution as live O＆M.
- 3. scene O＆M intelligent dispatching method as claimed in claim 1, it is characterised in that described according in the live O＆M Task, personnel and resource, generate multiple populations at random, specifically include：Judge whether the personnel meet personnel's constraints, and the personnel for meeting personnel's constraints are defined as effectively Personnel；Judge whether the task meets resource constraint, and be to have by the definition for the meeting the resource constraint of the task Effect task；According to the effectively task, effectively personnel and the resource, multiple populations are generated at random.
- 4. scene O＆M intelligent dispatching method as claimed in claim 3, it is characterised in that personnel's constraints includes institute State personnel and be in idle condition and perform the technical ability coefficient of the personnel of y procedures in the task and be higher than the y procedures Minimum requirements；The occupancy resource that the resource constraint includes the task is not more than the resource.
- 5. scene O＆M intelligent dispatching method as claimed in claim 2, it is characterised in that described to the multiple first of the population Beginning chromosome coding carry out non-dominated ranking operation, and according to the initial chromosome encode partial ordering relation select it is to be intersected Initial chromosome encodes, and specifically includes：The population is traveled through, multiple boundary sets are generated according to non-dominated ranking rule；The crowding distance encoded according to the multiple boundary set and the initial chromosome, to the initial chromosome in the population Coding is ranked up；Initial chromosome to be intersected is selected to encode according to the partial ordering relation that the initial chromosome after sequence encodes.
- 6. scene O＆M intelligent dispatching method as claimed in claim 5, it is characterised in that described according to described first after sequence The partial ordering relation of beginning chromosome coding selects initial chromosome to be intersected to encode, and specifically includes：When i-th initial chromosome coding when meeting default partial order condition, selects i-th with j-th initial chromosome coding A initial chromosome coding is encoded with j-th of initial chromosome coding as initial chromosome to be intersected；Wherein, it is described default Partial order condition be：Belong to different boundary sets and if only if i-th of initial chromosome coding and j-th of initial chromosome coding When, no more than j-th initial chromosome of sequence number that i-th of initial chromosome encodes corresponding boundary set encodes corresponding border The sequence number of collection, and the crowding distance of i-th of initial chromosome coding is more than the crowding distance of j-th of initial chromosome coding.
- 7. the live O＆M intelligent dispatching method as described in claim 5 or 6, it is characterised in that the scene O＆M is intelligently adjusted Degree method includes:Encoded according to the initial chromosome of adjacent two is encoded with i-th of initial chromosome in each target Range difference, calculate the crowding distance of i-th of initial chromosome coding.
- 8. scene O＆M intelligent dispatching method as claimed in claim 7, it is characterised in that the scene O＆M intelligent scheduling side Method includes:According to formulaCalculate the poly- of i-th initial chromosome coding Collect distance di；Wherein, di+1*fmIt is that the i+1 initial chromosome is encoded in m-th of sub-goal fmOn functional value, di-1*fmFor The i-1 initial chromosome codings are in m-th of sub-goal fmOn functional value.
- 9. scene O＆M intelligent dispatching method as claimed in claim 2, it is characterised in that described to waiting to hand over described in any two The initial chromosome coding of fork carries out crossover operation, and generation Cross reaction body coding, specifically includes：A hybridization point is randomly generated, will be located in initial chromosome coding to be mingled described in two after the hybridization point Code segment exchanges, and generates the Cross reaction body coding.
- 10. scene O＆M intelligent dispatching method as claimed in claim 2, it is characterised in that described to the Cross reaction body Coding carries out mutation operation, and generation child chromosome coding, specifically includes：A variable position is randomly generated, person number or the money of the variable position are corresponded to during the Cross reaction body is encoded Another person number or resource number of source numbering random replacement for same type, generate the child chromosome coding.
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