Dynamic and Heterogeneous Identity-Based Cooperative Co-Evolution for Distributed Lot-Streaming Flowshop Scheduling Problem

In this research, a novel dynamic and heterogeneous identity based cooperative co-evolutionary algorithm (DHICCA) is proposed for addressing the distributed lot-streaming flowshop scheduling problem (DLSFSP) with the objective to minimize the makespan. A two-layer-vector representation is devised to...

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Main Authors: Juan Wang, Guanghui Zhang, Xiaoling Li, Yanxiang Feng
Format: Article
Language:English
Published: Tsinghua University Press 2025-03-01
Series:Complex System Modeling and Simulation
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Online Access:https://www.sciopen.com/article/10.23919/CSMS.2024.0025
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author Juan Wang
Guanghui Zhang
Xiaoling Li
Yanxiang Feng
author_facet Juan Wang
Guanghui Zhang
Xiaoling Li
Yanxiang Feng
author_sort Juan Wang
collection DOAJ
description In this research, a novel dynamic and heterogeneous identity based cooperative co-evolutionary algorithm (DHICCA) is proposed for addressing the distributed lot-streaming flowshop scheduling problem (DLSFSP) with the objective to minimize the makespan. A two-layer-vector representation is devised to bridge the solution space of DLSFSP and the search space of DHICCA. In the evolution of DHICCA, population individuals are endowed with heterogeneous identities according to their quality, including superior individuals, ordinary individuals, and inferior individuals, which serve local exploitation, global exploration, and diversified restart, respectively. Because individuals with different identities require different evolutionary mechanisms to fully unleash their respective potentials, identity-specific evolutionary operators are devised to evolve them in a cooperative co-evolutionary way. This is important to use limited population resources to solve complex optimization problems. Specifically, exploitation is carried out on superior individuals by devising three exploitative operators with different intensities based on techniques of variable neighborhood, destruction-construction, and gene targeting. Exploration is executed on ordinary individuals by a newly constructed discrete Jaya algorithm and a probability crossover strategy. In addition, restart is performed on inferior individuals to introduce new evolutionary individuals to the population. After the cooperative co-evolution, all individuals with different identities are merged as a population again, and their identities are dynamically adjusted by new evaluation. The influence of parameters on the algorithm is investigated based on design-of-experiment and comprehensive computational experiments are used to evaluate the performance of all algorithms. The results validate the effectiveness of special designs and show that DHICCA performs more efficient than the existing state-of-the-art algorithms in solving the DLSFSP.
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institution Kabale University
issn 2096-9929
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spelling doaj-art-5e36ec7b47524af186855ded9b1472322025-08-20T03:40:17ZengTsinghua University PressComplex System Modeling and Simulation2096-99292097-37052025-03-01518610610.23919/CSMS.2024.0025Dynamic and Heterogeneous Identity-Based Cooperative Co-Evolution for Distributed Lot-Streaming Flowshop Scheduling ProblemJuan Wang0Guanghui Zhang1Xiaoling Li2Yanxiang Feng3School of Information Science and Technology, Hebei Agricultural University, Baoding 071001, ChinaSchool of Information Science and Technology, Hebei Agricultural University, Baoding 071001, ChinaSchool of Electronics and Control Engineering, Chang’an University, Xi’an 710064, ChinaSchool of Automation Science and Engineering, Xi’an Jiaotong University, Xi’an 710049, ChinaIn this research, a novel dynamic and heterogeneous identity based cooperative co-evolutionary algorithm (DHICCA) is proposed for addressing the distributed lot-streaming flowshop scheduling problem (DLSFSP) with the objective to minimize the makespan. A two-layer-vector representation is devised to bridge the solution space of DLSFSP and the search space of DHICCA. In the evolution of DHICCA, population individuals are endowed with heterogeneous identities according to their quality, including superior individuals, ordinary individuals, and inferior individuals, which serve local exploitation, global exploration, and diversified restart, respectively. Because individuals with different identities require different evolutionary mechanisms to fully unleash their respective potentials, identity-specific evolutionary operators are devised to evolve them in a cooperative co-evolutionary way. This is important to use limited population resources to solve complex optimization problems. Specifically, exploitation is carried out on superior individuals by devising three exploitative operators with different intensities based on techniques of variable neighborhood, destruction-construction, and gene targeting. Exploration is executed on ordinary individuals by a newly constructed discrete Jaya algorithm and a probability crossover strategy. In addition, restart is performed on inferior individuals to introduce new evolutionary individuals to the population. After the cooperative co-evolution, all individuals with different identities are merged as a population again, and their identities are dynamically adjusted by new evaluation. The influence of parameters on the algorithm is investigated based on design-of-experiment and comprehensive computational experiments are used to evaluate the performance of all algorithms. The results validate the effectiveness of special designs and show that DHICCA performs more efficient than the existing state-of-the-art algorithms in solving the DLSFSP.https://www.sciopen.com/article/10.23919/CSMS.2024.0025distributed flowshop schedulinglot-streaming schedulingidentity division and mergeheterogeneous evolutioncooperative co-evolution
spellingShingle Juan Wang
Guanghui Zhang
Xiaoling Li
Yanxiang Feng
Dynamic and Heterogeneous Identity-Based Cooperative Co-Evolution for Distributed Lot-Streaming Flowshop Scheduling Problem
Complex System Modeling and Simulation
distributed flowshop scheduling
lot-streaming scheduling
identity division and merge
heterogeneous evolution
cooperative co-evolution
title Dynamic and Heterogeneous Identity-Based Cooperative Co-Evolution for Distributed Lot-Streaming Flowshop Scheduling Problem
title_full Dynamic and Heterogeneous Identity-Based Cooperative Co-Evolution for Distributed Lot-Streaming Flowshop Scheduling Problem
title_fullStr Dynamic and Heterogeneous Identity-Based Cooperative Co-Evolution for Distributed Lot-Streaming Flowshop Scheduling Problem
title_full_unstemmed Dynamic and Heterogeneous Identity-Based Cooperative Co-Evolution for Distributed Lot-Streaming Flowshop Scheduling Problem
title_short Dynamic and Heterogeneous Identity-Based Cooperative Co-Evolution for Distributed Lot-Streaming Flowshop Scheduling Problem
title_sort dynamic and heterogeneous identity based cooperative co evolution for distributed lot streaming flowshop scheduling problem
topic distributed flowshop scheduling
lot-streaming scheduling
identity division and merge
heterogeneous evolution
cooperative co-evolution
url https://www.sciopen.com/article/10.23919/CSMS.2024.0025
work_keys_str_mv AT juanwang dynamicandheterogeneousidentitybasedcooperativecoevolutionfordistributedlotstreamingflowshopschedulingproblem
AT guanghuizhang dynamicandheterogeneousidentitybasedcooperativecoevolutionfordistributedlotstreamingflowshopschedulingproblem
AT xiaolingli dynamicandheterogeneousidentitybasedcooperativecoevolutionfordistributedlotstreamingflowshopschedulingproblem
AT yanxiangfeng dynamicandheterogeneousidentitybasedcooperativecoevolutionfordistributedlotstreamingflowshopschedulingproblem