Impact of Encoding and Neighborhood on Landscape Analysis for the Job Shop Scheduling Problem

被引:0
|
作者
Tsogbetse, Israel [1 ]
Bernard, Julien [2 ]
Manier, Herve [1 ]
Manier, Marie-Ange [1 ]
机构
[1] UTBM, CNRS, FEMTO ST, F-90010 Belfort, France
[2] UFC, CNRS, FEMTO ST, F-25000 Besancon, France
来源
IFAC PAPERSONLINE | 2022年 / 55卷 / 10期
关键词
optimization; job shop; encoding; neighborhood; fitness landscape; FITNESS LANDSCAPES; REPRESENTATIONS;
D O I
10.1016/j.ifacol.2022.09.559
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In order to improve the performance of metaheuristics, many studies focus on the efficiency of neighborhood operators and on the hybridization of various methods. Though, the solution encoding scheme has an important role in the search space's definition, their choice is usually made without any relevance study nor valuable justification. Thus, the present paper aims at conducting analysis on fitness landscapes generated by a basic job shop scheduling problem testing three encoding schemes combined with three operators to optimize the makespan scheduling criterion. Through the study of three different metrics, we show that the encoding schemes associated to neighborhood operators play a major role in the structure of the fitness landscape. Copyright (C) 2022 The Authors.
引用
收藏
页码:1237 / 1242
页数:6
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