An Improved Hyperplane Assisted Multiobjective Optimization for Distributed Hybrid Flow Shop Scheduling Problem in Glass Manufacturing Systems
作者机构：College of Computer ScienceLiaocheng UniversityLiaocheng252059China School of Information Science and EngineeringShandong Normal UniversityJinan25014China
出 版 物：《Computer Modeling in Engineering & Sciences》 (工程与科学中的计算机建模（英文）)
年 卷 期：2023年第134卷第1期
页 面：241-266页
核心收录：
主 题：Distributed hybrid flow shop energy consumption hyperplane-assisted multi-objective algorithm glass manufacturing system
摘 要：To solve the distributed hybrid flow shop scheduling problem(DHFS)in raw glass manufacturing systems,we investigated an improved hyperplane assisted evolutionary algorithm(IhpaEA).Two objectives are simultaneously considered,namely,the maximum completion time and the total energy ***,each solution is encoded by a three-dimensional vector,i.e.,factory assignment,scheduling,and machine ***,an efficient initialization strategy embeds two heuristics are developed,which can increase the diversity of the ***,to improve the global search abilities,a Pareto-based crossover operator is designed to take more advantage of non-dominated ***,a local search heuristic based on three parts encoding is embedded to enhance the searching *** enhance the local search abilities,the cooperation of the search operator is designed to obtain better non-dominated ***,the experimental results demonstrate that the proposed algorithm is more efficient than the other three state-of-the-art *** results show that the Pareto optimal solution set obtained by the improved algorithm is superior to that of the traditional multiobjective algorithm in terms of diversity and convergence of the solution.
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