Co-evolutionary Diversity Optimisation for the Traveling Thief Problem

被引:1
|
作者
Nikfarjam, Adel [1 ]
Neumann, Aneta [1 ]
Bossek, Jakob [2 ]
Neumann, Frank [1 ]
机构
[1] Univ Adelaide, Sch Comp Sci, Optimisat & Logist, Adelaide, SA, Australia
[2] Rhein Westfal TH Aachen, Dept Comp Sci, AI Methodol, Aachen, Germany
基金
澳大利亚研究理事会;
关键词
Quality diversity; Co-evolutionary algorithms; Evolutionary diversity optimisation; Traveling thief problem;
D O I
10.1007/978-3-031-14714-2_17
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Recently different evolutionary computation approaches have been developed that generate sets of high quality diverse solutions for a given optimisation problem. Many studies have considered diversity 1) as a mean to explore niches in behavioural space (quality diversity) or 2) to increase the structural differences of solutions (evolutionary diversity optimisation). In this study, we introduce a co-evolutionary algorithm to simultaneously explore the two spaces for the multi-component traveling thief problem. The results show the capability of the co-evolutionary algorithm to achieve significantly higher diversity compared to the baseline evolutionary diversity algorithms from the literature.
引用
收藏
页码:237 / 249
页数:13
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