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Metaheuristics for two-stage flow-shop assembly problem with a truncation learning function

ENGINEERING OPTIMIZATION 2021年第5期53卷 843-866页

作者： Wu, Chin-Chia Zhang, Xingong Azzouz, Ameni Shen, Wei-Lun Cheng, Shuenn-Ren Hsu, Peng-Hsiang Lin, Win-Chin Feng Chia Univ Dept Stat Taichung Taiwan Chongqing Normal Univ Coll Math Sci Chongqing Peoples R China Univ Tunis Inst Superieur Gest SMART Lab Tunis Tunisia Cheng Shiu Univ Grad Inst Business Adm Kaohsiung Taiwan Univ Kang Ning Dept Business Adm Taipei Taiwan

This study examines a two-stage three-machine flow-shop assembly scheduling model in which job processing time is considered as a mixed function of a controlled truncation parameter with a sum-of-processing-times-based learning effect. However, the truncation function is very limited in the two-stage flow-shop assembly scheduling settings. To overcome this limitation, this study investigates a two-stage three-machine flow-shop assembly problem with a truncation learning function where the makespan criterion (completion of the last job) is minimized. Given that the proposed model is NP hard, dominance rules, lemmas and a lower bound are derived and applied to the branch-and-bound method. A dynamic differential evolution algorithm, a hybrid greedy iterated algorithm and a genetic algorithm are also proposed for searching approximate solutions. Results obtained from test experiments validate the performance of all the proposed algorithms.

关键词： Two-stage assembly dynamic differential evolution algorithm genetic algorithm iterated greedy algorithm

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Managing Uncertainty and Disruptions in Resource Constrained Project Scheduling Problems: A Real-Time Reactive Approach

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IEEE ACCESS 2021年第99期9卷 45562-45586页

作者： Rahman, Md. Humyun Fuad Chakrabortty, Ripon K. Ryan, Michael J. UNSW Canberra ADFA Sch Engn & Informat Technol Capabil Syst Ctr Campbell ACT 2600 Australia

Resource constrained project scheduling problems (RCPSPs) are complex optimization problems that aim to minimize project completion time after considering limited resources and precedence-related activities with known durations. However, due to the dynamic nature of real-world applications, activity durations are vulnerable to change. In addition, resource demands along with resource availability at any stage of a project can also vary due to disruptions, which compel practitioners to re-think existing scheduling methodologies. Consequently, to mitigate the conjoint effect of those uncertainties and/or disruptions, this paper proposes a real-time reactive scheduling approach. To deal with uncertain activity durations, a chance constrained based approach is followed, which is later solved by an advanced meta-heuristic based approaches called IGFBIS and IGFBID. After solving an exhaustive list of stochastic RCPSP instances, this paper proves the efficacy of the proposed approaches, which is proven to be more useful to mitigate uncertainty or disruption while executing real-life projects.

关键词： Uncertainty Job shop scheduling Schedules Risk management Heuristic algorithms Electric breakdown Dynamic scheduling Scheduling real-life projects project scheduling with uncertainty and disruption iterated greedy algorithm chance constrained approach

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Local search-based metaheuristics for the robust distributed permutation flowshop problem

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APPLIED SOFT COMPUTING 2021年 105卷 107247-107247页

作者： Jing, Xue-Lei Pan, Quan-Ke Gao, Liang Shanghai Univ Sch Mechatron Engn & Automat Shanghai 200072 Peoples R China Liaocheng Univ Expt & Network Informat Ctr Liaocheng 252000 Shandong Peoples R China Liaocheng Univ Sch Comp Sci & Technol Liaocheng 252000 Shandong Peoples R China Huazhong Univ Sci & Technol State Key Lab Digital Mfg Equipment & Technol Wuhan 430074 Peoples R China

Distributed Permutation Flowshop Scheduling Problem (DPFSP) has become a hot issue in recent years. However, DPFSP with uncertain processing times (DPFSP_UPT) has not been addressed so far although real manufacturing systems often encounter various uncertain factors which make processing times uncertain. In this paper, two local-search based metaheuristics, i.e., an iterated greedy algorithm (sIG) and an iterated Local Search algorithm (sILS), are presented to solve the DPFSP_UPT with makespan criterion. A robust model of expect-risk rule is used to describe the DPFSP_UPT. A valid heuristic based on the well-known NEH heuristic is proposed to initialize sIG and sILS. An acceleration algorithm is adapted to save computational efforts. A destruction procedure with dynamic sizes is presented to enhance the exploration capability for sIG. A feature with the characteristic that small changes in the solution can preserve the properties of good solutions in the iterative process is applied by sILS. Both sIG and sILS use multiple local search methods to produce promising solutions by exploiting diverse search areas. Extensive experiments show that the proposed sIG and sILS perform significantly better than the five competing algorithms adapted in the literature, but there is no significant difference between sIG and sILS and each has its own advantages for different instances. (C) 2021 Elsevier B.V. All rights reserved.

关键词： Robust optimization Scenario iterated greedy algorithm iterated Local Search algorithm NEH heuristic

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iterated greedy algorithms for the blocking flowshop scheduling problem with makespan criterion

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COMPUTERS & OPERATIONS RESEARCH 2017年第0期77卷 111-126页

作者： Tasgetiren, M. Fatih Kizilay, Damla Pan, Quan-Ke Suganthan, P. N. Yasar Univ Dept Ind Engn Izmir Turkey Huazhong Univ Sci & Technol Wuhan Peoples R China Nanyang Technol Univ Sch Elect Singapore Singapore

Recently, iterated greedy algorithms have been successfully applied to solve a variety of combinatorial optimization problems. This paper presents iterated greedy algorithms for solving the blocking flowshop scheduling problem (BFSP) with the makespan criterion. Main contributions of this paper can be summed up as follows. We propose a constructive heuristic to generate an initial solution. The constructive heuristic generates better results than those currently in the literature. We employ and adopt well-known speed-up methods from the literature for both insertion and swap neighborhood structures. In addition, an iteration jumping probability is proposed to change the neighborhood structure from insertion neighborhood to swap neighborhood. Generally speaking, the insertion neighborhood is much more effective than the swap neighborhood for the permutation flowshop scheduling problems. Instead of considering the use of these neighborhood structures in a framework of the variable neighborhood search algorithm, two powerful local search algorithms are designed in such a way that the search process is guided by an iteration jumping probability determining which neighborhood structure will be employed. By doing so, it is shown that some additional enhancements can be achieved by employing the swap neighborhood structure with a speed-up method without jeopardizing the effectiveness of the insertion neighborhood. We also show that the performance of the iterated greedy algorithm significantly depends on the speed-up method employed. The parameters of the proposed iterated greedy algorithms are tuned through a design of experiments on randomly generated benchmark instances. Extensive computational results on Taillard's well-known benchmark suite show that the iterated greedy algorithms with speed-up methods are equivalent or superior to the best performing algorithms from the literature. Ultimately, 85 out of 120 problem instances are further improved with substantial marg

关键词： Meta-heuristics Blocking flowshop iterated greedy algorithm Variable neighborhood search Constructive heuristics

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Heuristic algorithms for a New and Practical Wire Rod and Bar Rolling Scheduling Problem 33

Heuristic Algorithms for a New and Practical Wire Rod and Ba...

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33rd Chinese Control and Decision Conference (CCDC)

作者： Zhao, Yafeng Zhao, Xianming Liu, Shixin Northeastern Univ State Key Lab Rolling & Automat Shenyang 110819 Peoples R China Northeastern Univ Coll Informat Sci & Engn State Key Lab Synthet Automat Proc Ind Shenyang 110819 Peoples R China

ISBN: (纸本)9781665440899

A scheduling problem in a wire rod and bar rolling process is very important and hard to solve in practical steel production systems. This paper considers a new scheduling problem originated from a wire rod and bar rolling process considering job release time and due time, as well as setup time between consecutive jobs. The objectives are to minimize both the number of late jobs and total setup times. Their linear combination is used to measure a schedule. To solve such a practical scheduling problem, four effective algorithms were designed. The experimental results show that all of the presented algorithms can well solve the considered problem. Among them, iterated greedy algorithm shows the best solution accuracy. Its great performance implies its readiness to be used in practical industrial scheduling systems.

关键词： Scheduling Problem Steel Rolling Process Heuristic algorithm Local Search iterated greedy algorithm

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Metaheuristics with restart and learning mechanisms for the no-idle flowshop scheduling problem with makespan criterion

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COMPUTERS & OPERATIONS RESEARCH 2022年 138卷 105616-105616页

作者： Oztop, Hande Tasgetiren, M. Fatih Kandiller, Levent Pan, Quan-Ke Izmir Demokrasi Univ Dept Ind Engn Izmir Turkey Yasar Univ Dept Int Logist Management Izmir Turkey Yasar Univ Dept Ind Engn Izmir Turkey Shanghai Univ Sch Mechatron Engn & Automat Shanghai 200072 Peoples R China Liaocheng Univ Sch Comp Sci Liaocheng 252000 Shandong Peoples R China

The no-idle permutation flowshop scheduling problem (NIPFSP) extends the well-known permutation flowshop scheduling problem, where idle time is not allowed on the machines. This study proposes a new mixed-integer linear programming (MILP) model and a new constraint programming (CP) model for the NIPFSP with makespan criterion. To the best of our knowledge, this study presents a CP model for the NIPFSP for the first time in the literature. We also compare the performance of the proposed MILP and CP models with a well-known MILP model from the literature. Since the studied problem is NP-hard, we also develop a new iterated greedy algorithm with restart and learning mechanisms (IG_RL) and a new iterated local search with restart and learning mechanisms (ILS_RL) as metaheuristics for the problem. In the proposed algorithms, all the parameters are determined by a learning mechanism in a self-adaptive way. Furthermore, a restart mechanism is employed in the proposed IG_RL and ILS_RL algorithms to guarantee the variety of the initial solutions and to assist the algorithm in avoiding the local optima. A variable neighborhood descent procedure is also embedded in the proposed algorithms. We use two well-known benchmark sets, i.e., VRF and Ruiz benchmark suites, to evaluate the performance of proposed solution methods. For almost half of the 240 small VRF instances, optimal results are reported by the MILP and CP models, whereas time-limited model results are reported for the rest. The results on small instances show that the proposed MILP and CP models outperform the MILP model from literature, where the CP model performs better than both MILP models. We compare the performance of the proposed IG_RL and ILS_RL algorithms with the state-of-the-art metaheuristics from the literature on both large VRF instances and Ruiz benchmark instances. The computational results show the effectiveness and superiority of the proposed ILS_RL and IG_RL algorithms for solving the NIPFSP. Primar

关键词： No-idle flowshop scheduling Makespan iterated greedy algorithm iterated local search Mathematical modeling Constraint programming

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The distributed flowshop scheduling problem with delivery dates and cumulative payoffs

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COMPUTERS & INDUSTRIAL ENGINEERING 2022年 165卷

作者： Li, Yuan-Zhen Pan, Quan-Ke He, Xuan Sang, Hong-Yan Gao, Kai-Zhou Jing, Xue-Lei Liaocheng Univ Sch Comp Sci Liaocheng 252059 Shandong Peoples R China Shanghai Univ Sch Mech Engn & Automat Shanghai 200072 Peoples R China Liaocheng Univ Expt & Network Informat Ctr Liaocheng 252059 Peoples R China

In the classic distributed permutation flowshop scheduling problem (DPFSP), there are more studies on the minimization of makespan, total flow time, total tardiness, etc. This paper studies a new problem with a new optimization goal, the DPFSP with delivery dates and cumulative payoffs. It is a variation of the DPFSP with job release dates that maximizes the total payoff with a stepwise job objective function. The main contributions are summarized as follows. (1) A mathematical model is built to formulate the new problem. (2) The characteristics of the problem are explored, and the upper and lower bounds of the problem are given. Based on the problem specific knowledge, an algorithm named Insert-Pruning is proposed to improve the efficiency of search. (3) Nine heuristic algorithms are proposed, including DRI, DRA, DEI, DEA, DNI, DNA, DII, DIA and DFF. (4) Combined with the characteristics of the problem, some modifications and improvements have been made to the IG algorithm to solve it, including the destruction method, the local search method and the acceptance criterion. (5) The experimental results show that the presented algorithm significantly outperforms the existing algorithms in the literature. In comparison with other competing algorithms in different dimensions, our algorithm has shown better performance, which verifies the effectiveness of this algorithm.

关键词： Distributed permutation flowshop scheduling Release time Delivery dates Cumulative payoffs Heuristics iterated greedy algorithm

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An effective iterated greedy method for the distributed permutation fl owshop scheduling problem with sequence-dependent setup times

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SWARM AND EVOLUTIONARY COMPUTATION 2020年 59卷

作者： Huang, Jiang-Ping Pan, Quan-Ke Gao, Liang Shanghai Univ Sch Mechatron Engn & Automat Shanghai 200072 Peoples R China Liaocheng Univ Sch Comp Sci Liaocheng 252000 Shandong Peoples R China Huazhong Univ Sci & Technol State Key Lab Digital Mfg Equipment & Technol Wuhan 430074 Peoples R China

The distributed permutation flowshop scheduling problem (DPFSP) has attracted much attention in recent years. In this paper, we extend the DPFSP by considering the sequence-dependent setup time (SDST), and present a mathematical model and an iterated greedy algorithm with a restart scheme (IGR). In the IGR, we discard the simulated annealing-like acceptance criterion commonly used in traditional iterated greedy algorithms. A restart scheme with six different operators is proposed to ensure the diversity of the solutions and help the algorithm to escape from local optimizations. Furthermore, to achieve a balance between the exploitation and exploration, we introduce an algorithmic control parameter in the IG stage. Additionally, to further improve the performance of the algorithm, we propose two local search methods based on a job block which is built in the evolution process. A detailed design experiment is carried out to calibrate the parameters for the presented IGR algorithm. The IGR is assessed through comparing with the state-of-the-art algorithms in the literature. The experimental results show that the proposed IGR algorithm is the best-performing one among all the algorithms in comparison.

关键词： Flowshop Scheduling iterated greedy algorithm Meta-heuristics

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Memetic algorithm for solving flexible flow-shop scheduling problems with dynamic transport waiting times

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COMPUTERS & INDUSTRIAL ENGINEERING 2020年 139卷 105984-000页

作者： Lei, Chuanjin Zhao, Ning Ye, Song Wu, Xiuli Univ Sci & Technol Beijing Sch Mech Engn Xueyuan Rd 30 Beijing 100083 Peoples R China

Flexible flow-shop scheduling with dynamic transport waiting times (FFSPDW) is a typical flow shop scheduling problem in smart manufacturing system. In this problem, jobs need to be transported by transporters like AGV (Automated Guided Vehicle) to next stage after processing. During transportation, waiting time dynamically occurs for both jobs and transporters, and finally contributes to makespan. The waiting times are conditioned by buffer capacity, machine allocations and production sequence. In order to minimize makespan with consideration of dynamic waiting times, we proposed a waiting time calculation approach to evaluate waiting time and makespan. This approach considers two situations: infinite buffer capacity and zero buffer capacity. Further, we developed a memetic algorithm integrated with waiting time calculation approach to solve FFSPDW. Finally, we verified the algorithm parameters via analysis of variance. Computational results show that the proposed memetic algorithm is able to reach high quality solutions with short computation time. Consequently, the proposed approach is suitable for solving industrial FFSPDW problems.

关键词： Flexible flow-shop scheduling Dynamic waiting times Integrated scheduling iterated greedy algorithm Makespan

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An effective multi-AGVs dispatching method applied to matrix manufacturing workshop

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COMPUTERS & INDUSTRIAL ENGINEERING 2022年 163卷

作者： Zhang, Xu-jin Sang, Hong-yan Li, Jun-qing Han, Yu-yan Duan, Peng Liaocheng Univ Sch Comp Sci Liaocheng 252059 Shandong Peoples R China

This paper studies the problem of multiple automatic guided vehicles (multi-AGVs) dispatching in a matrix manufacturing workshop. The goal is to minimize the transportation cost that includes the cost of travelling distance, the cost of penalty time and the cost of AGVs. For the purpose, a mixed integer linear programming model is set up and an improved iterated greedy (IIG) algorithm is proposed. In the algorithm, an AGV route merging strategy and a workshop partition strategy are designed to reduce the cost of AGVs and travelling distance. Two rules are designed to quickly identify infeasible solutions to save the operation time. A nearest neighbor heuristic is used to generate an initial solution with high quality. In the local search stage, four effective operators are used to improve the quality of the solution. A repair strategy is proposed to avoid the algorithm falling into local optima. Finally, we use 110 real instances to test the IIG and the other six algorithms in the literature. The comparative experiments show that the proposed algorithm and strategies have much better performance for solving this problem.

关键词： Matrix manufacturing workshops Multi-AGVs iterated greedy algorithm Dispatching

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