CN117371769B - Scheduling acceleration evaluation method for distributed blocking flow shop - Google Patents
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Abstract
The invention discloses a distributed blocking flow shop scheduling acceleration evaluation method, which relates to the technical field of shop scheduling and takes a distributed blocking flow shop with sequence related preparation time as an example to construct an acceleration evaluation method based on the inter-factory exchange, the intra-factory exchange and the inter-factory insertion neighborhood of an energy consumption cost target; comprising the following steps: step 1: calculating a forward departure time of a workpiece on a machine in a factory and a maximum finishing time before using an exchange or insertion neighborhood; step 2: calculating the backward departure time of the workpiece on the machine in the factory; step 3: calculating the maximum finishing time after using the exchange or inserting the neighborhood; step 4: calculating the variable quantity of the processing, preparing and standby energy consumption cost after using the exchange or inserting neighborhood in the factory; step 5: calculating the maximum energy consumption cost in all factories; step 6: and (5) evaluating the energy consumption cost. The method solves the problem of target acceleration evaluation of the energy consumption cost of the distributed blocking flow shop scheduling.
Description
Technical Field
The invention relates to the technical field of workshop scheduling, in particular to a distributed blocking flow workshop scheduling acceleration evaluation method based on an energy consumption cost target.
Background
In the global background, collaborative production modes among companies are becoming more and more common, and the traditional centralized production mode cannot meet market demands. Accordingly, the centralized production mode gradually changes to the distributed production mode. The mode breaks the regional limitation and fully utilizes the resources of a plurality of enterprises or factories so as to realize reasonable configuration, optimized combination and sharing of the resources. Distributed manufacturing has practical application in a variety of fields, such as automotive manufacturing, furniture manufacturing, electronic device manufacturing, and semiconductor manufacturing. Distributed manufacturing involves collaboration and coordination between multiple geographically dispersed workshops or plants, and this decentralized nature results in a significant increase in the complexity and challenges of task scheduling and resource coordination. To address the complexity in a distributed manufacturing environment, distributed flow shop scheduling problems are presented. The problem aims to solve task scheduling and resource coordination among a plurality of geographically dispersed workshops or factories so as to realize the optimization of the high efficiency and the resource utilization rate of the whole production process.
As energy prices are expected to rise substantially over a long period of time, manufacturing industry has begun to prioritize the problem of energy consumption costs. In existing distributed blocking flow shop scheduling problem studies based on energy cost objectives, switching and inserting neighborhood operations are generally considered as common methods for obtaining high quality scheduling sequences. However, the process of recalculating the energy consumption cost after using the exchange or inserting the neighborhood is complicated, so that a large amount of calculation is caused, a large amount of optimal scheduling time is consumed, the optimal scheduling method is not fully utilized, the scheduling sequence is unreasonable, idle production lines can be caused, the production time is increased, and the production efficiency is reduced. Meanwhile, insufficient or wasteful resource utilization may increase production cost, affect product quality, reduce processing accuracy, and affect product quality. However, few studies currently consider designing a corresponding accelerated evaluation method for this problem, thereby reducing the time complexity of solving the energy costs. Therefore, this is an important practical problem to be solved.
Disclosure of Invention
In order to better solve the problem of acceleration evaluation of the energy consumption cost target of the distributed blocking flow shop scheduling with the sequence related preparation time, an effective acceleration evaluation method is provided, namely, the energy consumption cost target-based distributed blocking flow shop scheduling acceleration evaluation method is divided into an inter-factory exchange acceleration criterion, an intra-factory exchange acceleration criterion and an inter-factory insertion acceleration criterion according to the problem constraint and the characteristics of the energy consumption cost target.
The invention provides a distributed blocking flow shop scheduling acceleration evaluation method based on an energy consumption cost target, which comprises the following steps:
step 1: calculating the forward departure time of all the workpieces in the factory on the machine and the maximum finishing time before using the exchange or insertion neighborhood;
step 2: calculating backward departure time of all workpieces in the factory on the machine;
step 3: calculating a forward departure time and a maximum completion time after using the exchange or inserting the neighborhood;
step 4: calculating the variable quantity of the processing energy consumption cost, the preparation energy consumption cost and the standby energy consumption cost after using exchange or inserting neighborhood in a factory;
step 5: calculating the maximum energy consumption cost of all factories according to the maximum finishing time before and after using the exchange or inserting the neighborhood, the processing energy consumption cost, the preparation energy consumption cost and the change quantity of standby energy consumption cost；
Step 6: evaluation of。
Further, the acceleration evaluation method is classified into an inter-plant exchange acceleration criterion, an intra-plant exchange acceleration criterion, and an inter-plant insertion acceleration criterion according to the characteristics of the problem constraint and the energy consumption cost target.
Further, the inter-factory exchange acceleration criteria include:
attempting to exchange factory f a First of (a) a Work pieces and factory f b First of (a) b The maximum energy consumption cost is minimized by the workpieces; wherein f a ＞0，f b ＞0，l a ＞0，l b ＞0；
Step 11: calculating a plant f a And factory f b Forward departure time of all work pieces on machine m，And using maximum finishing time before factory exchange neighborhood，；
Step 12: calculating a plant f a And factory f b Backward departure time of all work pieces on machine m，；
Step 13: suppose for plant f a And factory f b Calculating a forward departure time using the factory exchange neighborhood，And maximum finishing time，；
Step (a)14: calculating the change amounts of the post-processing energy consumption cost, the preparation energy consumption cost and the standby energy consumption cost of the factory exchange neighborhood，，，，，；
Step 15: according to plant f a And factory f b Calculating the maximum energy consumption cost in all factories by using the variation of the maximum finishing time, the processing energy consumption cost, the preparation energy consumption cost and the standby energy consumption cost before and after the neighborhood exchange in the factories；
Step 16: evaluation ofWhether or not to be improved, ifImproved acceptance of the exchange, otherwise re-at plant f a And factory f b One workpiece each attempts to exchange and repeats steps 13, 14, 15, 16 until the exchange is accepted.
Further, in the step 11, the plant f a And factory f b Forward departure time of all work pieces on machine m，And using maximum finishing time before factory exchange neighborhood，The calculation formula of (2) is as follows:
wherein,indicating the forward completion time of the first workpiece on machine m in factory f,indicating the preparation time of the first-1 workpiece and the first workpiece on machine m in factory f,indicating the processing time of the first workpiece on machine m in factory f,the number of work pieces in the factory f is represented, and m is an integer.
Further, in the step 12, the plant f a And factory f b Backward finishing time of all the work pieces on machine m，The calculation formula of (2) is as follows:
wherein,the backward completion time of the first workpiece on machine m in factory f.
Further, in the step 13, the assumption is made for the plant f a And factory f b Calculating a forward departure time using the factory exchange neighborhood，And maximum finishing time，The calculation formula of (2) is as follows:
wherein,representing the forward completion time on machine m of the first workpiece in factory f after the factory exchange neighborhood is used.
Further, in the step 14, after the neighborhood is exchanged between the factories, the amount of change in the processing energy cost, the preparation energy cost, and the standby energy cost is calculated，，，，，The calculation formula of (2) is as follows:
wherein,represents the unit energy consumption cost of the factory f,represents the energy consumption per unit time of machining the first workpiece by the machine m in the factory f,representing the energy consumption per unit time from the first-1 st workpiece to the first workpiece in the machine m in the factory f,indicating the energy consumption per unit time of the machine m in the standby state.
Further, in the step 15, the maximum energy consumption cost in all the factoriesThe calculation formula of (2) is as follows:
wherein,andrespectively represent the factory f a And factory f b Using the energy costs before exchanging neighborhoods between plants,andrespectively represent the factory f a And factory f b Energy costs after exchanging neighborhoods between plants are used.
Further, the in-plant exchange acceleration criteria include:
attempting to exchange the t-th workpiece and the k-th workpiece in the factory f, so that the maximum energy consumption cost is minimum; wherein f is more than 0, t is more than 0, k is more than 0, t is more than k, and t is not equal to k;
step 21: calculating the forward departure time of all the workpieces on machine m in factory fAnd using maximum finishing time before exchanging neighborhood in factory；
Step 22: calculating the backward departure time of all the workpieces on machine m in factory f；
Step 23: assuming the t-th workpiece and the k-th workpiece in the swap factory f, calculating the forward departure time after using the swap neighborhood in the factoryAnd maximum finishing time；
Step 24: calculating the change amounts of the processing energy consumption cost, the preparation energy consumption cost and the standby energy consumption cost after using the exchange neighborhood in the factory，，；
Step 25: calculating the maximum energy consumption cost in all factories according to the maximum finishing time and the processing energy consumption cost before and after the factory f uses the exchange neighborhood in the factory, the preparation energy consumption cost and the change quantity of standby energy consumption cost；
Step 26: evaluation ofWhether or not to be improved, ifThe improvement accepts the swap, otherwise reattempting to select two different workpiece swaps in factory f and repeating steps 23, 24, 25, 26 until the swap is accepted.
Further, in the step 21, the forward departure time of all the workpieces in the factory f on the machine m is calculatedAnd using maximum finishing time before exchanging neighborhood in factoryThe calculation formula is as follows:
further, in step 22, the backward finishing time of all the workpieces in the factory f on machine mThe calculation formula is as follows:
further, in the step 23, the t-th workpiece and the k-th workpiece in the assumed exchange factory f are used to calculate the forward departure time after the use of the factory exchange neighborhoodAnd maximum finishing timeThe calculation formula is as follows:
further, in the step 24, the calculating uses the change amounts of the processing energy consumption cost, the preparation energy consumption cost and the standby energy consumption cost after the factory exchange neighborhood，，The calculation formula is as follows:
further, in said step 25, the maximum energy consumption cost in said all factoriesThe calculation formula of (2) is as follows:
further, the inter-factory insertion acceleration criteria include:
attempting to apply an external workpieceInserted into the factory f, so as to minimize the maximum energy consumption cost; wherein f > 0;
step 31: calculating the forward departure time of all the workpieces on machine m in factory fAnd using maximum finishing time before inserting neighborhood between factories；
Step 32: calculating the backward departure time of all the workpieces on machine m in factory f；
Step 33: assume a workpieceInserted into the k-position of the factory f,calculating a forward departure time after using an inter-factory interpolation neighborhoodAnd maximum finishing time；
Step 34: calculating the change quantity of the processing energy consumption cost, the preparation energy consumption cost and the standby energy consumption cost after inserting the neighborhood between factories，，；
Step 35: calculating the maximum energy consumption cost in all factories according to the variable quantity of the maximum finishing time before and after the factory f uses the factory to insert the neighborhood and the processing energy consumption cost, the preparation energy consumption cost and the standby energy consumption cost；
Step 36: repeating steps 33, 34, 35 until all positionsAre all evaluated and the workpiece is processedInserted into the factory f at the position where the maximum energy consumption cost is minimum.
Further, in the step 31, the forward departure time of all the workpieces in the factory f on the machine m is calculatedAnd using maximum finishing time before inserting neighborhood between factoriesThe calculation formula is as follows:
further, in the step 32, the backward finishing time of all the workpieces in the factory f on the machine mThe calculation formula is as follows:
further, in the step 33, the forward departure time after the neighborhood is exchanged in the factory is usedAnd maximum finishing timeThe calculation formula is as follows:
further, in the step 34, the factory f uses factory-to-factory insertion neighborhood to process the energy cost, prepare the energy cost, wait forVariable of energy consumption cost，，The calculation formula is as follows:
further, in said step 35, the maximum energy consumption cost in said all factoriesThe calculation formula of (2) is as follows:
；
the distributed blocking flow shop scheduling acceleration evaluation method based on the energy consumption cost target has the following technical effects:
the method comprises the following steps:
(1) The invention digs the hidden problem characteristic, take distributed blocking flow shop with related preparation time of the sequence as an example, analyze and use and insert or exchange the influence in the goal course of the cost of energy to calculate the problem constraint, divide the accelerating evaluation method into the factory exchange accelerating rule, factory exchange accelerating rule and factory insertion accelerating rule according to the characteristic of problem constraint and cost of energy goal;
(2) Assuming that the factory exchange neighborhood is in progressAfter the exchange attempt, the exchange is accepted, and the time complexity is reduced from that of the factory by using the inter-factory exchange acceleration criteriaIs reduced to；
(3) Assuming that the intra-factory exchange neighborhood is in progressAfter the exchange attempt, the exchange is accepted, and the time complexity is reduced from that of the factory by using the in-factory exchange acceleration criteriaIs reduced to；
(4) Temporal complexity is decoupled from using inter-factory insertion acceleration criteriaIs reduced to；
(5) The maximum energy consumption cost in all factories is rapidly calculated by using the maximum finishing time and the processing energy consumption cost before and after the neighborhood is exchanged or inserted in the factories, and the change amounts of the preparation energy consumption cost and the standby energy consumption cost.
Application level:
(1) The invention provides an acceleration evaluation method for reducing the complexity of calculation time, obviously shortening the calculation time and improving the calculation efficiency, which has obvious superiority compared with the traditional calculation mode;
(2) In the same optimization time, the scheduling scheme using the acceleration evaluation method provided by the invention can perform more iterative optimization, fully mine the potential of the optimized scheduling method, obtain a more accurate scheduling scheme, and avoid errors in the scheduling process;
(3) The invention can efficiently schedule and optimize workshop tasks according to production requirements, and minimizes the maximum energy consumption cost by optimizing a scheduling scheme, thereby balancing the energy consumption cost of factories or workshops in different areas, helping enterprises to reasonably allocate resources and energy sources, and improving the scheduling efficiency of workshops;
(4) The optimized scheduling scheme can reduce the idle time of materials and equipment, improve the stability and reliability of a production line, and effectively reduce resource waste, thereby remarkably reducing production cost and energy consumption cost.
Therefore, the invention provides a distributed blocking flow shop scheduling acceleration evaluation method based on an energy consumption cost target. Taking a distributed blocking flow shop with starting time as an example, the method constructs an acceleration evaluation method of inter-factory exchange, intra-factory exchange and insertion neighborhood based on the energy consumption cost target, effectively reduces the evaluation time of the energy consumption cost target, and improves the scheduling efficiency of the shop. In addition, the method and the device solve the problem of acceleration evaluation of the energy consumption cost target of the flow shop scheduling, and provide a good solution for the acceleration evaluation of the energy consumption cost target of the flow shop scheduling.
Specific embodiments of the invention are disclosed in detail below with reference to the following description and drawings, indicating the manner in which the principles of the invention may be employed. It should be understood that the embodiments of the invention are not limited in scope thereby.
Features that are described and/or illustrated with respect to one embodiment may be used in the same way or in a similar way in one or more other embodiments in combination with or instead of the features of the other embodiments.
It should be emphasized that the term "comprises/comprising" when used herein is taken to specify the presence of stated features, integers, steps or components but does not preclude the presence or addition of one or more other features, integers, steps or components.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions of the prior art, the drawings which are used in the description of the embodiments or the prior art will be briefly described, it being obvious that the drawings in the description below are only some embodiments of the invention, and that other drawings can be obtained from these drawings without inventive faculty for a person skilled in the art.
FIG. 1 provides a small scale example Gantt chart according to one embodiment of the present invention.
FIG. 2 provides a schematic representation of the forward departure time of a workpiece on a machine in accordance with one embodiment of the invention.
FIG. 3 provides a schematic representation of the backward departure time of a workpiece on a machine in accordance with one embodiment of the invention.
FIG. 4 is a graph of confidence interval comparisons for a plant number grouping, according to one embodiment of the present invention.
Detailed Description
In order to make the technical solution of the present invention better understood by those skilled in the art, the technical solution of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, shall fall within the scope of the invention.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and/or" as used herein includes any and all combinations of one or more of the associated listed items.
The present invention is described below with reference to flowchart illustrations and/or block diagrams of methods, systems, and computer program products according to embodiments of the invention. It will be understood that some blocks of the flowchart illustrations and/or block diagrams, and combinations of some blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be stored or implemented in a microcontroller, microprocessor, digital Signal Processor (DSP), field Programmable Gate Array (FPGA), state machine, programmable Logic Controller (PLC) or other processing circuit, general purpose computer, special purpose computer. The use computer or other programmable data processing apparatus (e.g., a production machine) to create means or block diagrams for implementing the functions/acts specified in the flowchart and/or block diagrams by the instructions being executed by the processor of the computer or other programmable data processing apparatus.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means. The functions/acts specified in the flowchart and/or block diagram block or blocks are implemented.
The computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus. Other programmable devices provide steps for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. It should be understood that the functions/acts noted in the blocks may occur out of the order noted in the operational illustrations. For example, two blocks shown in succession may in fact be executed substantially concurrently or the blocks may sometimes be executed in the reverse order, depending upon the functionality/acts involved. Although some of the figures include arrows on the communication paths to illustrate the primary direction of communication, it should be understood that communication may occur in a direction opposite to the depicted arrows.
The specific implementation process of the invention is as follows:
taking a small scale example of a distributed blocked flow shop scheduling problem as an example, assume that the example contains 11 workpieces, the 11 workpieces are to be distributed to 3 plants for processing, each plant is a flow shop containing 3 machines, and the processing order of all the workpieces is the same. The starting time of the current workpiece is closely related to the last processed workpiece. There is no buffer between the machines, so the workpiece remains on the current machine even if processing is completed on the current machine unless the next machine is in an idle state. One possible scheduling scheme is that the workpieces 2,4,7,8,9, 10 are processed in the factory 1 in the processing sequence of 9- > 8- > 2- > 4- > 10- > 7, the workpieces 1,3, 11 are processed in the factory 2 in the processing sequence of 11- > 3- > 1, and the workpieces 5,6 are processed in the factory 3 in the processing sequence of 6- > 5, the Gantt chart of which is shown in fig. 1.
The invention provides a distributed blocking flow shop scheduling acceleration evaluation method based on an energy consumption cost target, which comprises the following steps:
step 1: calculating the forward departure time of all the workpieces in the factory on the machine and the maximum finishing time before using the exchange or insertion neighborhood;
step 2: calculating backward departure time of all workpieces in the factory on the machine;
step 3: calculating a forward departure time and a maximum completion time after using the exchange or inserting the neighborhood;
step 4: calculating the variable quantity of the processing energy consumption cost, the preparation energy consumption cost and the standby energy consumption cost after using exchange or inserting neighborhood in a factory;
step 5: calculating the maximum energy consumption cost of all factories according to the maximum finishing time before and after using the exchange or inserting the neighborhood, the processing energy consumption cost, the preparation energy consumption cost and the change quantity of standby energy consumption cost；
Step 6: evaluation of。
Wherein, the schematic diagram of the forward departure time of the workpiece on the machine is shown in fig. 2, and the schematic diagram of the backward departure time of the workpiece on the machine is shown in fig. 3.
Specifically, taking a distributed blocking flow shop with a sequence related preparation time as an example, the method mainly comprises the following implementation processes:
dividing an acceleration evaluation method into an inter-factory exchange acceleration criterion, an intra-factory exchange acceleration criterion and an inter-factory insertion acceleration criterion according to the characteristics of the problem constraint and the energy consumption cost target;
in some embodiments of the present application, the inter-factory exchange acceleration criteria include:
attempting to exchange factory f a First of (a) a Work pieces and factory f b First of (a) b The maximum energy consumption cost is minimized by the workpieces; wherein f a ＝1，2，3，f b ＝1，2，3，f a ≠f b ，l a ＞0，l b ＞0；
Step 11: calculating a plant f a And factory f b Forward departure time of all work pieces on machine m，And using maximum finishing time before factory exchange neighborhood，The calculation formula is as follows. It should be noted that the maximum finishing time may be achieved by various methods in the prior art, and the following is only an example.
Wherein,representing the forward completion time of the aluminum of the first order in the plant f on machine m,representing the preparation time of the first-1 order and the first order on machine m in factory f,indicating the processing time of the first workpiece on machine m in factory f,representing the number of workpieces in a factory f, wherein m is an integer;
step 12: calculating a plant f a And factory f b Backward departure time of all work pieces on machine m，The calculation formula is as follows:
wherein,backward completion time of the first workpiece on machine m in factory f;
step 13: suppose for plant f a And factory f b Calculating a forward departure time using the factory exchange neighborhood，And maximum finishing time，The calculation formula is as follows:
wherein,representing the forward completion time on machine m of the first workpiece in factory f after the use of the factory exchange neighborhood;
step 14: calculating the change quantity of the post-processing energy consumption cost, the preparation energy consumption cost and the standby energy consumption cost of the factory exchange neighborhood，，，，，The calculation formula is as follows:
wherein,represents the unit energy consumption cost of the factory f,represents the energy consumption per unit time of machining the first workpiece by the machine m in the factory f,representing the energy consumption per unit time from the first-1 st workpiece to the first workpiece in the machine m in the factory f,representing the energy consumption per unit time of the machine m in a standby state;
step 15: according to plant f a And factory f b Calculating the maximum energy consumption cost in all factories by using the variation of the maximum finishing time, the processing energy consumption cost, the preparation energy consumption cost and the standby energy consumption cost before and after the neighborhood exchange in the factoriesThe calculation formula is as follows:
wherein,andrespectively represent the factory f a And factory f b Using factory-to-factory switching neighborsThe cost of energy consumption in front of the domain,andrespectively represent the factory f a And factory f b Energy consumption cost after the neighborhood is exchanged between factories is used;
step 16: evaluation ofWhether or not to be improved, ifImproved acceptance of the exchange, otherwise re-at plant f a And factory f b One workpiece each attempts to exchange and repeats steps 13, 14, 15, 16 until the exchange is accepted.
Some embodiments of the present application assume that the factory-to-factory switching neighborhood is in progressAfter the exchange attempt, the exchange is accepted. Time complexity is decoupled from using inter-factory exchange acceleration criteriaIs reduced to。
In some embodiments of the present application, the in-plant exchange acceleration criteria include:
attempting to exchange the t-th workpiece and the k-th workpiece in the factory f, so that the maximum energy consumption cost is minimum; wherein f=1, 2,3, t > 0, k > 0, t > k, t+.k;
step 21: calculating the forward departure time of all the workpieces on machine m in factory fAnd using maximum finishing time before exchanging neighborhood in factoryThe calculation formula is as follows. It should be noted that the maximum finishing time may be achieved by various methods in the prior art, and the following is only an example.
Step 22: calculating the backward departure time of all the workpieces on machine m in factory fThe calculation formula is as follows:
step 23: assuming the t-th workpiece and the k-th workpiece in the swap factory f, calculating the forward departure time after using the swap neighborhood in the factoryAnd maximum finishing timeThe calculation formula is as follows:
step 24: calculating the change amount of the processing energy consumption cost, the preparation energy consumption cost and the standby energy consumption cost after using the exchange neighborhood in the factory，，The calculation formula is as follows:
step 25: calculating the maximum energy consumption cost in all factories according to the variable quantity of the maximum finishing time, the processing energy consumption cost, the preparation energy consumption cost and the standby energy consumption cost before and after the factory f uses the exchange neighborhood in the factoryThe calculation formula is as follows:
；
step 26: evaluation ofWhether or not to be improved, ifThe improvement accepts the swap, otherwise reattempting to select two different workpiece swaps in factory f and repeating steps 23, 24, 25, 26 until the swap is accepted.
Some embodiments of the present application assume that the in-factory exchange neighborhood is in progressAfter the exchange attempt, the exchange is accepted. Time complexity is decoupled from using in-plant exchange acceleration criteriaIs reduced to。
In some embodiments of the present application, the inter-factory insertion acceleration criteria include:
attempting to apply an external workpieceInserted into the factory f, so as to minimize the maximum energy consumption cost; wherein f=1, 2,3;
step 31: calculating the forward departure time of all the workpieces on machine m in factory fAnd using maximum finishing time before inserting neighborhood between factories；
Step 32: calculating the backward departure time of all the workpieces on machine m in factory f；
Step 33: assume a workpieceInserted into the k-position of the factory f,calculating a forward departure time after using an inter-factory interpolation neighborhoodAnd maximum finishing timeThe calculation formula is as follows:
step 34: calculating the change quantity of the processing energy consumption cost, the preparation energy consumption cost and the standby energy consumption cost after inserting the neighborhood between factories，，The calculation formula is as follows:
step 35: calculating the maximum energy consumption cost in all factories according to the variable quantity of the maximum finishing time before and after the factory f uses the factory to insert the neighborhood and the processing energy consumption cost, the preparation energy consumption cost and the standby energy consumption costThe calculation formula is as follows:
step 36: repeating steps 33, 34, 35 until all positionsAre all evaluated and the workpiece is processedInserted into the factory f at the position where the maximum energy consumption cost is minimum.
Some embodiments of the present application slave time complexity by using inter-factory insertion acceleration criteriaIs reduced to。
The maximum energy consumption cost in all factories is rapidly calculated by using the maximum finishing time and the processing energy consumption cost before and after the neighborhood is exchanged or inserted in the factories, the preparation energy consumption cost and the standby energy consumption cost.
FIG. 4 is a comparison of confidence intervals for a plant number packet of the present invention, wherein A-DABC applies the proposed accelerated evaluation method and A-DABC_no does not apply the proposed fast evaluation method; ARPI represents the average relative percentage deviation (Average relative percentage increase) as the final evaluation index of the performance, and the calculation formula of the ARPI is as followsWherein, the method comprises the steps of, wherein,representing the maximum energy consumption cost obtained when a specific algorithm solves a specific exampleThe minimum maximum energy consumption cost obtained when solving the same calculation example is represented in all the used algorithms; specifically, as can be seen from the ARPI values of FIG. 4, the ARPI results of A-DABC are significantly better than those of A-DABC_no. The method accelerates the calculation time of the energy consumption cost target, fully exerts the algorithm performance, and can converge to the best value at a higher convergence rate.
It is to be understood that the above description is intended to be illustrative, and not restrictive. Many embodiments and many applications other than the examples provided will be apparent to those of skill in the art upon reading the above description. The scope of the present teachings should, therefore, be determined not with reference to the above description, but instead should be determined with reference to the appended claims, along with the full scope of equivalents to which such claims are entitled. The disclosures of all articles and references, including patent applications and publications, are incorporated herein by reference for the purpose of completeness. The omission of any aspect of the subject matter disclosed herein in the preceding claims is not intended to forego such subject matter, nor should the inventors regard such subject matter as not be considered to be part of the disclosed subject matter.
Claims (1)
1. The distributed blocking flow shop scheduling acceleration evaluation method based on the energy consumption cost target is characterized by comprising the following steps of:
step 1: calculating the forward departure time of all the workpieces in the factory on the machine and the maximum finishing time before using the exchange or insertion neighborhood;
step 2: calculating backward departure time of all workpieces in the factory on the machine;
step 3: calculating a forward departure time and a maximum completion time after using the exchange or inserting the neighborhood;
step 4: calculating the variable quantity of the processing energy consumption cost, the preparation energy consumption cost and the standby energy consumption cost after using exchange or inserting neighborhood in a factory;
step 5: calculating the maximum energy consumption cost of all factories according to the maximum finishing time before and after using the exchange or inserting the neighborhood, the processing energy consumption cost, the preparation energy consumption cost and the change quantity of standby energy consumption cost；
Step 6: evaluation of；
The acceleration evaluation method comprises an inter-factory exchange acceleration criterion, an inter-factory insertion acceleration criterion and an intra-factory exchange acceleration criterion;
the inter-plant exchange acceleration criteria include:
attempting to exchange factory f a First of (a) a Work pieces and factory f b First of (a) b The maximum energy consumption cost is minimized by the workpieces; wherein f a ＞0，f b ＞0，l a ＞0，l b ＞0；
Step 11: computing factoryf a And factory f b Forward departure time of all work pieces on machine m，/>And maximum finishing time before exchanging neighborhood between factories +.>，/>；
Step 12: calculating a plant f a And factory f b Backward departure time of all work pieces on machine m，；
Step 13: suppose for plant f a And factory f b Calculating a forward departure time using the factory exchange neighborhood，/>And maximum finishing time->，/>；
Step 14: calculating the change quantity of the post-processing energy consumption cost, the preparation energy consumption cost and the standby energy consumption cost of the factory exchange neighborhood，/>，/>，/>，/>，/>；
Step 15: according to plant f a And factory f b Calculating the maximum energy consumption cost in all factories by using the variation of the maximum finishing time, the processing energy consumption cost, the preparation energy consumption cost and the standby energy consumption cost before and after the neighborhood exchange in the factories；
Step 16: evaluation ofWhether or not to be improved, if->Improved acceptance of the exchange, otherwise re-at plant f a And factory f b One workpiece is selected to be exchanged and the steps 13, 14, 15, 16 are repeated until the exchange is accepted;
in the step 12, the plant f a And factory f b Backward finishing time of all the work pieces on machine m，/>The calculation formula of (2) is as follows:
wherein (1)>Backward completion time of the first workpiece on machine m in factory f, +.>Representing the preparation time of the first-1 st workpiece and the first workpiece on machine m in factory f, <>Indicating the processing time of the first workpiece on machine m in factory f,representing the number of workpieces in a factory f, wherein m is an integer;
in the step 13, the assumption is made for the plant f a And factory f b Calculating a forward departure time using the factory exchange neighborhood，/>And maximum finishing time->，/>The calculation formula of (2) is as follows:
wherein,representing the forward completion time on machine m of the first workpiece in factory f after the use of the factory exchange neighborhood;
in the step 14, after the neighborhood is exchanged between factories, the amount of change in the process energy cost, the preparation energy cost, and the standby energy cost，/>，/>，/>，/>，/>The calculation formula of (2) is as follows:
wherein,representing the unit energy consumption cost of the plant f, +.>Representing the energy consumption per unit time of machine m processing the first workpiece in factory f, +.>Representing the energy consumption per unit time from the first-1 st workpiece to the first workpiece in the machine m in the factory f, +.>Representing the energy consumption per unit time of the machine m in a standby state;
in the step 15, the maximum energy consumption cost in all factoriesThe calculation formula of (2) is as follows:
wherein (1)>And->Respectively represent the factory f a And factory f b Energy costs before exchanging neighborhoods between factories, < >>And->Respectively represent the factory f a And factory f b Energy consumption cost after the neighborhood is exchanged between factories is used;
the in-plant exchange acceleration criteria include:
attempting to exchange the t-th workpiece and the k-th workpiece in the factory f, so that the maximum energy consumption cost is minimum; wherein f is more than 0, t is more than 0, k is more than 0, t is more than k, and t is not equal to k;
step 21: calculating the forward departure time of all the workpieces on machine m in factory fAnd maximum finishing time before exchanging neighborhood in factory>；
Step 22: all work pieces in the computing factory f are on-machineBackward departure time on m；
Step 23: assuming the t-th workpiece and the k-th workpiece in the swap factory f, calculating the forward departure time after using the swap neighborhood in the factoryAnd maximum finishing time->；
Step 24: calculating the change amounts of the processing energy consumption cost, the preparation energy consumption cost and the standby energy consumption cost after using the exchange neighborhood in the factory，/>，/>；
Step 25: calculating the maximum energy consumption cost in all factories according to the maximum finishing time and the processing energy consumption cost before and after the factory f uses the exchange neighborhood in the factory, the preparation energy consumption cost and the change quantity of standby energy consumption cost；
Step 26: evaluation ofWhether or not to be improved, if->Accepting the swap if improved, otherwise reattempting to select two different workpiece swaps in factory f and repeating steps 23, 24, 25, 26 until accepting the swap;
further, in the step 21, the forward departure time of all the workpieces in the factory f on the machine m is calculatedAnd maximum finishing time before exchanging neighborhood in factory>The calculation formula is as follows:
；
in step 22, the backward finishing time of all the workpieces in the factory f on machine mThe calculation formula is as follows:
in the step 23, the t-th workpiece and the k-th workpiece in the factory f are assumed to be exchanged, and the forward departure time ∈>And maximum finishing time->The calculation formula is as follows:
in the step 24, the calculation uses the change amount of the processing energy consumption cost, the preparation energy consumption cost and the standby energy consumption cost after the neighborhood is exchanged in the factory ≡>，/>，/>The calculation formula is as follows:
in said step 25, the maximum energy costs in said all factories are +.>The calculation formula of (2) is as follows:
；
the inter-factory insertion acceleration criteria include:
attempting to apply an external workpieceInserted into the factory f, so as to minimize the maximum energy consumption cost; wherein f > 0;
step 31: calculating the forward departure time of all the workpieces on machine m in factory fAnd maximum finishing time before inserting neighborhood in factory>；
Step 32: calculating the backward departure time of all the workpieces on machine m in factory f；
Step 33: assume a workpieceInserted into k position of factory f, +.>Calculating the forward departure time after using the factory-to-factory insertion neighborhood>And maximum finishing time->；
Step 34: calculating the change quantity of the processing energy consumption cost, the preparation energy consumption cost and the standby energy consumption cost after inserting the neighborhood between factories，/>，/>；
Step 35: calculating the maximum energy consumption cost in all factories according to the variable quantity of the maximum finishing time before and after the factory f uses the factory to insert the neighborhood and the processing energy consumption cost, the preparation energy consumption cost and the standby energy consumption cost；
Step 36: repeating steps 33, 34, 35 until all positionsAre all evaluated and work piece +.>Inserting the position with the minimum maximum energy consumption cost in the factory f;
in the step 32, the backward finishing time of all the workpieces in the factory f on the machine mThe calculation formula is as follows:
；
wherein,backward completion time of the first workpiece on machine m in factory f, +.>Representing the preparation time of the first and the (1) th work piece on machine m in factory f, <>Representing the processing time of the first workpiece on machine m in factory f, +.>Representing the number of workpieces in a factory f, wherein m is an integer;
in the step 33, the forward departure time after the neighborhood is exchanged in the factory is usedAnd maximum finishing timeThe calculation formula is as follows:
in the step 34, the factory f uses the variables of the factory-to-factory insertion neighborhood post-processing energy consumption cost, the preparation energy consumption cost and the standby energy consumption cost，/>，/>The calculation formula is as follows:
；
。
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Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US10743198B1 (en) * | 2018-01-22 | 2020-08-11 | North Carolina Agricultural And Technical State University | Transportation infrastructure location and redeployment |
| CN114839930A (en) * | 2022-03-17 | 2022-08-02 | 兰州理工大学 | Integrated dispatching system for distributed assembly blocking flow workshop |
| CN115249113A (en) * | 2021-12-15 | 2022-10-28 | 聊城大学 | Distributed zero-waiting flow shop scheduling method and system with preparation time |
| CN115309111A (en) * | 2021-12-13 | 2022-11-08 | 聊城大学 | Resource-limited distributed hybrid flow shop scheduling method and system |
| CN115933568A (en) * | 2022-12-27 | 2023-04-07 | 河南工业大学 | Multi-target distributed hybrid flow shop scheduling method |
| CN116011726A (en) * | 2022-11-21 | 2023-04-25 | 山东师范大学 | Distributed non-waiting workshop scheduling optimization method and system for solving problem of tape delivery |
| CN116307629A (en) * | 2023-04-07 | 2023-06-23 | 聊城大学 | Quick evaluation method for flow shop grouping scheduling |
| CN116629509A (en) * | 2023-04-07 | 2023-08-22 | 聊城大学 | Flow shop grouping scheduling rapid evaluation method based on key machine |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6640088B2 (en) * | 2001-12-14 | 2003-10-28 | Motorola, Inc. | Method and system for adaptive channel estimation techniques |
| DE102015202451A1 (en) * | 2015-02-11 | 2016-08-11 | Volkswagen Aktiengesellschaft | Device and method for accelerating a vehicle when starting at a traffic light system |
-
2023
- 2023-12-08 CN CN202311674386.XA patent/CN117371769B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US10743198B1 (en) * | 2018-01-22 | 2020-08-11 | North Carolina Agricultural And Technical State University | Transportation infrastructure location and redeployment |
| CN115309111A (en) * | 2021-12-13 | 2022-11-08 | 聊城大学 | Resource-limited distributed hybrid flow shop scheduling method and system |
| CN115249113A (en) * | 2021-12-15 | 2022-10-28 | 聊城大学 | Distributed zero-waiting flow shop scheduling method and system with preparation time |
| CN114839930A (en) * | 2022-03-17 | 2022-08-02 | 兰州理工大学 | Integrated dispatching system for distributed assembly blocking flow workshop |
| CN116011726A (en) * | 2022-11-21 | 2023-04-25 | 山东师范大学 | Distributed non-waiting workshop scheduling optimization method and system for solving problem of tape delivery |
| CN115933568A (en) * | 2022-12-27 | 2023-04-07 | 河南工业大学 | Multi-target distributed hybrid flow shop scheduling method |
| CN116307629A (en) * | 2023-04-07 | 2023-06-23 | 聊城大学 | Quick evaluation method for flow shop grouping scheduling |
| CN116629509A (en) * | 2023-04-07 | 2023-08-22 | 聊城大学 | Flow shop grouping scheduling rapid evaluation method based on key machine |
Non-Patent Citations (3)
| Title |
|---|
| Discrete differential evolution algorithm for distributed blocking flowshop scheduling with makespan criterion;Zhang, Guanghui;《Engineering Applications of Artificial Intelligence》;20181130;第76卷;第96-107页 * |
| 一种解决有限缓冲区流水车间调度问题的复合启发式算法;张培文;段俊华;李俊青;;聊城大学学报(自然科学版);20120625(第02期);全文 * |
| 不确定工时下多目标柔性作业车间调度问题的进化求解方法;钟小玉;《中国科学》;20230412;第53卷(第4期);第737-757页 * |
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