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FLEXIBLE JOB-SHOP SCHEDULING WITH FUZZY GOAL THROUGH IOCDGA 被引量:1
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作者 袁坤 朱剑英 孙志峻 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI 2006年第2期144-148,共5页
The fuzzy goal flexible job-shop scheduling problem (FGFJSP) is the extension of FJSP. Compared with the convention JSP, it can solve the fuzzy goal problem and meet suit requirements of the key job. The multi-objec... The fuzzy goal flexible job-shop scheduling problem (FGFJSP) is the extension of FJSP. Compared with the convention JSP, it can solve the fuzzy goal problem and meet suit requirements of the key job. The multi-object problem, such as the fuzzy cost, the fuzzy due-date, and the fuzzy makespan, etc, can be solved by FGFJSP. To optimize FGFJSP, an individual optimization and colony diversity genetic algorithm (IOCDGA) is presented to accelerate the convergence speed and to avoid the earliness. In IOCDGA, the colony average distance and the colony entropy are defined after the definition of the encoding model. The colony diversity is expressed by the colony average distance and the colony entropy. The crossover probability and the mutation probability are controlled by the colony diversity. The evolution emphasizes that sigle individual or a few individuals evolve into the best in IOCDGA, but not the all in classical GA. Computational results show that the algorithm is applicable and the number of iterations is less. 展开更多
关键词 genetic algorithm flexible job-shop scheduling fuzzy goal
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INTEGRATED OPERATOR GENETIC ALGORITHM FOR SOLVING MULTI-OBJECTIVE FLEXIBLE JOB-SHOP SCHEDULING
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作者 袁坤 朱剑英 +1 位作者 鞠全勇 王有远 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI 2006年第4期278-282,共5页
In the flexible job-shop scheduling problem (FJSP), each operation has to be assigned to a machine from a set of capable machines before alocating the assigned operations on all machines. To solve the multi-objectiv... In the flexible job-shop scheduling problem (FJSP), each operation has to be assigned to a machine from a set of capable machines before alocating the assigned operations on all machines. To solve the multi-objective FJSP, the Grantt graph oriented string representation (GOSR) and the basic manipulation of the genetic algorithm operator are presented. An integrated operator genetic algorithm (IOGA) and its process are described. Comparison between computational results and the latest research shows that the proposed algorithm is effective in reducing the total workload of all machines, the makespan and the critical machine workload. 展开更多
关键词 flexible job-shop integrated operator genetic algorithm multi-objective optimization job-shop scheduling
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Simultaneous scheduling of machines and automated guided vehicles in flexible manufacturing systems using genetic algorithms 被引量:5
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作者 I.A.Chaudhry S.Mahmood M.Shami 《Journal of Central South University》 SCIE EI CAS 2011年第5期1473-1486,共14页
The problem of simultaneous scheduling of machines and vehicles in flexible manufacturing system (FMS) was addressed.A spreadsheet based genetic algorithm (GA) approach was presented to solve the problem.A domain inde... The problem of simultaneous scheduling of machines and vehicles in flexible manufacturing system (FMS) was addressed.A spreadsheet based genetic algorithm (GA) approach was presented to solve the problem.A domain independent general purpose GA was used,which was an add-in to the spreadsheet software.An adaptation of the propritary GA software was demonstrated to the problem of minimizing the total completion time or makespan for simultaneous scheduling of machines and vehicles in flexible manufacturing systems.Computational results are presented for a benchmark with 82 test problems,which have been constructed by other researchers.The achieved results are comparable to the previous approaches.The proposed approach can be also applied to other problems or objective functions without changing the GA routine or the spreadsheet model. 展开更多
关键词 automated guided vehicles (AGVs) scheduling job-shop genetic algorithms flexible manufacturing system (FMS) SPREADSHEET
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Hybrid heuristic algorithm for multi-objective scheduling problem 被引量:3
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作者 PENG Jian'gang LIU Mingzhou +1 位作者 ZHANG Xi LING Lin 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2019年第2期327-342,共16页
This research provides academic and practical contributions. From a theoretical standpoint, a hybrid harmony search(HS)algorithm, namely the oppositional global-based HS(OGHS), is proposed for solving the multi-object... This research provides academic and practical contributions. From a theoretical standpoint, a hybrid harmony search(HS)algorithm, namely the oppositional global-based HS(OGHS), is proposed for solving the multi-objective flexible job-shop scheduling problems(MOFJSPs) to minimize makespan, total machine workload and critical machine workload. An initialization program embedded in opposition-based learning(OBL) is developed for enabling the individuals to scatter in a well-distributed manner in the initial harmony memory(HM). In addition, the recursive halving technique based on opposite number is employed for shrinking the neighbourhood space in the searching phase of the OGHS. From a practice-related standpoint, a type of dual vector code technique is introduced for allowing the OGHS algorithm to adapt the discrete nature of the MOFJSP. Two practical techniques, namely Pareto optimality and technique for order preference by similarity to an ideal solution(TOPSIS), are implemented for solving the MOFJSP.Furthermore, the algorithm performance is tested by using different strategies, including OBL and recursive halving, and the OGHS is compared with existing algorithms in the latest studies.Experimental results on representative examples validate the performance of the proposed algorithm for solving the MOFJSP. 展开更多
关键词 flexible job-shop scheduling HARMONY SEARCH (HS) algorithm PARETO OPTIMALITY opposition-based learning
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An Improved Genetic Algorithm for Solving the Mixed⁃Flow Job⁃Shop Scheduling Problem with Combined Processing Constraints 被引量:4
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作者 ZHU Haihua ZHANG Yi +2 位作者 SUN Hongwei LIAO Liangchuang TANG Dunbing 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI CSCD 2021年第3期415-426,共12页
The flexible job-shop scheduling problem(FJSP)with combined processing constraints is a common scheduling problem in mixed-flow production lines.However,traditional methods for classic FJSP cannot be directly applied.... The flexible job-shop scheduling problem(FJSP)with combined processing constraints is a common scheduling problem in mixed-flow production lines.However,traditional methods for classic FJSP cannot be directly applied.Targeting this problem,the process state model of a mixed-flow production line is analyzed.On this basis,a mathematical model of a mixed-flow job-shop scheduling problem with combined processing constraints is established based on the traditional FJSP.Then,an improved genetic algorithm with multi-segment encoding,crossover,and mutation is proposed for the mixed-flow production line problem.Finally,the proposed algorithm is applied to the production workshop of missile structural components at an aerospace institute to verify its feasibility and effectiveness. 展开更多
关键词 mixed-flow production flexible job-shop scheduling problem(FJSP) genetic algorithm ENCODING
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Distributed Flexible Job-Shop Scheduling Problem Based on Hybrid Chemical Reaction Optimization Algorithm 被引量:1
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作者 Jialei Li Xingsheng Gu +1 位作者 Yaya Zhang Xin Zhou 《Complex System Modeling and Simulation》 2022年第2期156-173,共18页
Economic globalization has transformed many manufacturing enterprises from a single-plant production mode to a multi-plant cooperative production mode.The distributed flexible job-shop scheduling problem(DFJSP)has bec... Economic globalization has transformed many manufacturing enterprises from a single-plant production mode to a multi-plant cooperative production mode.The distributed flexible job-shop scheduling problem(DFJSP)has become a research hot topic in the field of scheduling because its production is closer to reality.The research of DFJSP is of great significance to the organization and management of actual production process.To solve the heterogeneous DFJSP with minimal completion time,a hybrid chemical reaction optimization(HCRO)algorithm is proposed in this paper.Firstly,a novel encoding-decoding method for flexible manufacturing unit(FMU)is designed.Secondly,half of initial populations are generated by scheduling rule.Combined with the new solution acceptance method of simulated annealing(SA)algorithm,an improved method of critical-FMU is designed to improve the global and local search ability of the algorithm.Finally,the elitist selection strategy and the orthogonal experimental method are introduced to the algorithm to improve the convergence speed and optimize the algorithm parameters.In the experimental part,the effectiveness of the simulated annealing algorithm and the critical-FMU refinement methods is firstly verified.Secondly,in the comparison with other existing algorithms,the proposed optimal scheduling algorithm is not only effective in homogeneous FMUs examples,but also superior to existing algorithms in heterogeneous FMUs arithmetic cases. 展开更多
关键词 scheduling problem distributed flexible job-shop chemical reaction optimization algorithm heterogeneous factory simulated annealing algorithm
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A hybrid genetic algorithm for multi-objective flexible job shop scheduling problem considering transportation time 被引量:8
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作者 Xiabao Huang Lixi Yang 《International Journal of Intelligent Computing and Cybernetics》 EI 2019年第2期154-174,共21页
Purpose–Flexible job-shop scheduling is significant for different manufacturing industries nowadays.Moreover,consideration of transportation time during scheduling makes it more practical and useful.The purpose of th... Purpose–Flexible job-shop scheduling is significant for different manufacturing industries nowadays.Moreover,consideration of transportation time during scheduling makes it more practical and useful.The purpose of this paper is to investigate multi-objective flexible job-shop scheduling problem(MOFJSP)considering transportation time.Design/methodology/approach–A hybrid genetic algorithm(GA)approach is integrated with simulated annealing to solve the MOFJSP considering transportation time,and an external elitism memory library is employed as a knowledge library to direct GA search into the region of better performance.Findings–The performance of the proposed algorithm is tested on different MOFJSP taken from literature.Experimental results show that proposed algorithm performs better than the original GA in terms of quality of solution and distribution of the solution,especially when the number of jobs and the flexibility of the machine increase.Originality/value–Most of existing studies have not considered the transportation time during scheduling of jobs.The transportation time is significantly desired to be included in the FJSP when the time of transportation of jobs has significant impact on the completion time of jobs.Meanwhile,GA is one of primary algorithms extensively used to address MOFJSP in literature.However,to solve the MOFJSP,the original GA has a possibility to get a premature convergence and it has a slow convergence speed.To overcome these problems,a new hybrid GA is developed in this paper. 展开更多
关键词 flexible job-shop scheduling problem Transportation time Genetic algorithm Simulated annealing Multi-objective optimization
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考虑批量装配的柔性作业车间调度问题研究 被引量:8
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作者 巴黎 李言 +2 位作者 曹源 杨明顺 刘永 《中国机械工程》 EI CAS CSCD 北大核心 2015年第23期3200-3207,共8页
柔性作业车间调度是生产调度领域中的一个重要组合优化问题,由于取消了工序与加工设备的唯一性对应关系,因而相较于作业车间调度问题,具有更高的复杂度。针对该问题在批量装配方面的不足,考虑将批量因素与装配环节同时集成到柔性作业车... 柔性作业车间调度是生产调度领域中的一个重要组合优化问题,由于取消了工序与加工设备的唯一性对应关系,因而相较于作业车间调度问题,具有更高的复杂度。针对该问题在批量装配方面的不足,考虑将批量因素与装配环节同时集成到柔性作业车间调度问题当中。以成品件的完工时间为优化目标,对该批量装配柔性作业车间调度问题进行了数学建模。针对该模型,提出一种多层编码结构的粒子群算法,并对该算法的各个模块进行了设计。最后,以实例验证了该数学模型的正确性及算法的有效性。 展开更多
关键词 柔性作业车间调度问题 批量 装配 6 层编码结构 flexible job-shop scheduling PROBLEM (FJSP)
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