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An Improved Multi-Objective iterated greedy algorithm for Energy-Efficient Distributed Permutation Flowshop Scheduling Problem with Sequence-dependent Setup Times 36

An Improved Multi-Objective Iterated Greedy Algorithm for En...

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36th Chinese Control and Decision Conference (CCDC)

作者： Zhong, Quan Yu, Yang Hang, YanZhao Shenyang Aerosp Univ Sch Automat Shenyang Peoples R China

ISBN: (纸本)9798350387780;9798350387797

Distributed energy-efficient scheduling has gained a lot of focus in industrial production in recent years. However, energy-efficient distributed permutation flowshop scheduling problem (EEDPFSP) with sequence-dependent setup time is closer to the actual manufacturing environment and has not attracted much attention so far. In this paper, energy-efficient distributed permutation flowshop scheduling problem with sequence-dependent setup time is investigated. An improved multi-objective NEH heuristic and an improved multi-objective iterated greedy algorithm (IMOIG) are proposed to minimize both total flowtime and total energy consumption. Effective construction, destruction and local search procedures are proposed in combination with a speed-scaling framework. Based on the sequence characteristics of the problem, the method of job block moving is proposed for local search. Finally, the effectiveness of the proposed algorithm is demonstrated through computational experiments by comparing with other four algorithms.

关键词： Energy-efficient distributed scheduling Sequence dependent iterated greedy algorithm Multi-objective

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A Reinforcement Learning Driven iterated greedy algorithm for Energy-Efficiency Flexible Job-Shop Scheduling Problem 4

A Reinforcement Learning Driven Iterated Greedy Algorithm fo...

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4th International Conference on Computer, Control and Robotics (ICCCR)

作者： Bao, Haizhu Wang, Chuang Pan, Quanke Wang, Bingtao Rong, Miao Yang, Aolei Wang, Xiaohua Shanghai Univ Sch Mechatron Engn & Automat Shanghai Peoples R China

ISBN: (纸本)9798350373141;9798350373158

The escalating environmental challenges have sparked significant interest in energy-efficient scheduling as a potent strategy for realizing sustainable development and fostering green manufacturing. This approach is characterized by its dual focus on economic efficiency and energy conservation. This paper tackles the energy-efficient scheduling of the flexible job-shop scheduling problem (EFJSP) with the dual objective of minimizing both makespan and total energy consumption. The mixed-integer linear programming (MILP) model of EFJSP is devised. A reinforcement learning driven iterated greedy algorithm (RLIGA) is proposed to solve the EFJSP. Furthermore, upon a thorough analysis of the problem's characteristics, two optimization strategies-a energy-saving strategy and an acceleration strategy-are developed to enhance the solution further. Extensive benchmark tests have substantiated the superior efficiency and significance of the RLIGA over state-of-the-art algorithms in addressing the EFJSP.

关键词： flexible job-shop energy-efficient scheduling iterated greedy algorithm reinforcement learning multi-objective optimization

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A parallel-optimized iterated greedy algorithm for blocking hybrid flow shop scheduling problem 35

A parallel-optimized iterated greedy algorithm for blocking ...

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35th Chinese Control and Decision Conference (CCDC)

作者： Wang, Yong Wang, Yuting Li, Chengshuai Zhang, Chenyao Wang, Yuhang Liaocheng Univ Sch Comp Sci Liaocheng Shandong Peoples R China

ISBN: (纸本)9798350334722

We study the blocking hybrid flow shop scheduling problem (BHFSP) aiming at maximum completion time in this paper, which has practical implications in the manufacturing industry. A parallel-optimized iterated greedy (POIG) algorithm is presented to optimize the objective of minimizing the maximum completion time. The whole POIG algorithm adopts a parallel scheme to increase the solution diversity. First, the NEH and MME heuristics are used to initialize the two solutions;subsequently, to strengthen the performance of the POIG and make machine blocking timeless, two permutation-based local perturbation strategies are proposed;using simulated annealing (SA) algorithm to increase the solution diversity. The proposed algorithm is tested against other algorithms on 100 instance sets of different scales. The final simulation experiments show that the POIG performs better than other comparison algorithms, and it can be considered as an effective solution to the BHFSP.

关键词： Blocking parallel optimization iterated greedy algorithm hybrid flow shop scheduling problem makespan

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Scheduling of distributed blocking flowshop with setup times using a Two-stage perturbation iterated greedy algorithm 35

Scheduling of distributed blocking flowshop with setup times...

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35th Chinese Control and Decision Conference (CCDC)

作者： Zhang, Chenyao Wang, Yuting Wang, Yuhang Wang, Yong Li, Chengshuai Yang, Feng Liaocheng Univ Sch Comp Sci Liaocheng Shandong Peoples R China Zhongtong Bus Holding Co Ltd Paint Shop Liaocheng Shandong Peoples R China

ISBN: (纸本)9798350334722

The limitations of the centralized production model and the advancement of mass customization production models are guiding the manufacturing industry toward a distributed production pattern. This article aims to solve the distributed blocking flowshop scheduling problem with sequence-dependent setup times, called DBFSP_SDST. Specifically, a Two-stage perturbation iterated greedy algorithm (TIG) is developed to optimize maximum completion time. In TIG, a mechanism with self-adaptive thinking is developed in global perturbation process and an efficient insertion operator is presented in local perturbation process. After counting extensive experimental results, the proposed TIG outperforms the existing state-of-the-art algorithms in solving the considered problem.

关键词： blocking distributed flowshop iterated greedy algorithm makespan

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An iterated greedy algorithm Based on Accelerated Calculation for Distributed Flowshop Group Scheduling Problem with Blocking Constraints 35

An Iterated Greedy Algorithm Based on Accelerated Calculatio...

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35th Chinese Control and Decision Conference (CCDC)

作者： Wang, Yizheng Wang, Yuting Wang, Yuhang Ji, Qianhui Liaocheng Univ Sch Comp Sci Liaocheng Shandong Peoples R China

ISBN: (纸本)9798350334722

Today's industrial production models are becoming increasingly complex. Jobs of the same type are usually divided into groups for machining. Factories are often designed in a distributed structure, i.e., they are built in serval different locations. The distributed flowshop group scheduling problem with blocking constraints (DBFGSP) has not been well studied. We constructed a mixed-integer linear programming model, and an iterated greedy algorithm based on the accelerated calculation (IGACA) to reduce the time complexity. We use 810 instances to compare our proposed algorithm with four other excellent algorithms used to solve related problems. The experimental result shows that our proposed algorithm is advantageous in solving the DBFGSP.

关键词： distributed blocking flowshop group scheduling problem iterated greedy algorithm makespan acceleration calculation

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An effective population-based iterated greedy algorithm for solving the multi-AGV scheduling problem with unloading safety detection

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INFORMATION SCIENCES 2024年 657卷

作者： Zou, Wenqiang Zou, Jiazhen Sang, Hongyan Meng, Leilei Pan, Quanke Liaocheng Univ Sch Comp Sci Liaocheng 252000 Peoples R China Shanghai Univ Sch Mechatron Engn & Automat Shanghai 200072 Peoples R China

With the increasing prevalence of automated guided vehicles (AGVs), the multi-AGV scheduling problem has become a hot research topic in recent years. However, little attention has been devoted to unloading safety detection for multi-AGV scheduling. This paper investigates a multiAGV scheduling problem with unloading safety detection (MAGVSUSD) in a matrix manufacturing workshop. The aim is to minimize the total cost composed of travel cost, penalty cost and cost of AGV used. To address the MAGVSUSD, a mixed-integer linear programming model and a population-based iterated greedy (PIG) algorithm are proposed. In the PIG, a hyper-heuristic based on neighborhood operators and a population-based initialization method are proposed to obtain multiple high-quality initial solutions. The two-stage destruction strategy is designed to avoid falling into the local optimal solution and to enhance its ability to explore a larger solution space. The two-choice reconstruction strategy is developed to obtain better neighbor solutions by switching the search landscape. The local search based on the winning neighbor operators is proposed to dynamically adapt to each distribution situation in the workshop. A large number of experimental results demonstrate the proposed algorithm's superiority over existing algorithms in addressing the considered problem.

关键词： Automated guided vehicle iterated greedy algorithm Safety detection Unloading setup time Scheduling

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A tabu memory based iterated greedy algorithm for the distributed heterogeneous permutation flowshop scheduling problem with the total tardiness criterion

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EXPERT SYSTEMS WITH APPLICATIONS 2024年第PartD期238卷

作者： Feng, Xiaobing Zhao, Fei Jiang, Gedong Tao, Tao Mei, Xuesong Xi An Jiao Tong Univ Sch Mech Engn Xian 710049 Shaanxi Peoples R China

Distributed scheduling problems have been extensively studied due to their critical roles in industrial applications. Most research focuses on identical distributed factories and the objective of minimizing the makespan, ignoring the widely existing heterogeneous factories and delivery targets in reality. This paper aims to establish a distributed heterogeneous flowshop scheduling scenario with the objective of minimizing total tardiness (DHPFSP-t), and solve it using an improved iterative greedy algorithm. A mixed-integer programming model and several problem-specific properties are proposed for this novel scheduling scenario. Based on the distributed heterogeneous characteristics of the problem, four constructive algorithms are established to quickly generate initial solutions. Among them, the better solution is selected as the initial solution of the iterative greedy algorithm. To enhance the performance of the iterative greedy algorithm, the concept of tabu memory is incorporated and novel destruction and local search processes are devised. Thorough experiments are conducted to verify the effectiveness of the mixed-integer programming model of the scenario, the constructive heuristics and the improved iterative greedy algorithm. The result confirms the validity of the proposed model and the good performance of the proposed method.

关键词： Distributed heterogeneous Tabu memory iterated greedy algorithm Total tardiness

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Regionalization of primary health care units: An iterated greedy algorithm for large-scale instances

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EXPERT SYSTEMS WITH APPLICATIONS 2024年 250卷

作者： Mendoza-Gomez, Rodolfo Rios-Mercado, Roger Z. Tecnol Monterrey Sch Engn & Sci Eugenio Garza Sada SN Guanajuato 37190 Mexico Univ Autonoma Nuevo Leon UANL Grad Program Elect Engn Ave Univ S-nCd Univ San Nicolas De Los Garza 66455 Nuevo Leon Mexico

In this paper, we study the problem of multi -institutional regionalization of primary health care units. The problem consists of deciding where to place new facilities, capacity expansions for existing facilities, and demand allocation in a multi -institutional system to minimize the total travel distance from demand points to health care units. It is known that traditional exact methods as branch -and -bound are limited to solving small- to medium -size instances of the problem. Given that real world -instances can be large, in this paper we propose an iterated greedy algorithm with variable neighborhood descent search for handling large-scale instances. Within this solution framework, several methods are developed. A greedy constructive method and two deconstruction strategies are developed. Another interesting component is the exact optimization of a demand allocation subproblem that is obtained when the location of facilities is previously fixed. An empirical assessment using real -world data from the State of Mexico's Public Health Care System is carried out. The results demonstrate the effectiveness of the proposed metaheuristic in handling large-scale instances.

关键词： Public health care planning Facility location Metaheuristics iterated greedy algorithm

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Minimizing Total Tardiness in the Distributed Flowshop Group Scheduling Problem with an iterated greedy algorithm 34

Minimizing Total Tardiness in the Distributed Flowshop Group...

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34th Chinese Control and Decision Conference (CCDC)

作者： Wang, Zhi-Yuan Pan, Yiran Pan, Quan-Ke Shanghai Univ Sch Mech & Elect Engn & Automat Shanghai 200444 Peoples R China Shanghai Lixin Univ Accounting & Finance Sch Informat Management Shanghai 201209 Peoples R China Liaocheng Univ Sch Comp Sci Liaocheng 252000 Peoples R China

ISBN: (纸本)9781665478960

This paper studies a distributed permutation flowshop group scheduling problem (DPFGSP) with a total tardiness criterion, which has significant applications in the current manufacturing environment. The considered problem can be broken down into three sub-problems: how to assign the families to each factory, how to determine the sequence of the families within each factory, and the processing order of jobs within each family. The paper proposes an effective two-stage iterated greedy algorithm (FJIG) to minimize the total tardiness time for the DPFGSP and utilizes an improved NEH heuristic to generate an initial solution for the proposed FJIG. Comprehensive statistical experiments are carried out to test the effectiveness of the FJIG and the experimental results demonstrate that the proposed FJIG is very effective for the DPFGSP with total tardiness criterion.

关键词： Distributed group scheduling tardiness time metaheuristic iterated greedy algorithm

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An improved iterated greedy algorithm for the distributed assembly permutation flowshop scheduling problem

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COMPUTERS & INDUSTRIAL ENGINEERING 2021年 152卷 107021-107021页

作者： Huang, Ying-Ying Pan, Quan-Ke Huang, Jiang-Ping Suganthan, P. N. Gao, Liang Shanghai Univ Sch Mech & Elect Engn & Automat Shanghai 200444 Peoples R China Liaocheng Univ Sch Comp Sci Liaocheng 252000 Shandong Peoples R China Nanyang Technol Univ Sch Elect & Elect Engn Singapore 639798 Singapore Huazhong Univ Sci & Technol State Key Lab Digital Mfg Equipment & Technol Wuhan 430074 Peoples R China

This paper considers a distributed assembly permutation flowshop scheduling problem (DAPFSP) with total flowtime (TF) criterion, which is of great significance to both industry and research community. We propose an improved iterative greedy algorithm based on the groupthink (gIGA) for solving the problem. Firstly, based on the solution representation, we present an effective initialization procedure by combining the well-known NEH heuristic and Palmer method. Secondly, in order to improve the efficiency of the algorithm, both the destruction reconstruction process and the local search process are elaborately designed for the products and jobs separately. Next, our algorithm adaptively extracts jobs in the destruction stage with regard to the size of instances. In addition, we employ a novel selection method that is based on the objective values and the ages of the individuals in the population. Through a total of 810 benchmark instances, the proposed algorithm is compared with seven state-of-the-art algorithms in the literature. The experimental results show that the proposed algorithm performs significantly better than the other algorithms in comparison by three analytical methods for solving the DAPFSP with TF criterion.

关键词： Distributed assembly permutation flowshop scheduling Total flowtime iterated greedy algorithm Heuristic Local search

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