Evolutionary Diversity Optimisation for The Traveling Thief Problem

• URL: http://arxiv.org/abs/2204.02709v1
• Date: Wed, 6 Apr 2022 10:13:55 GMT
• Title: Evolutionary Diversity Optimisation for The Traveling Thief Problem
• Authors: Adel Nikfarjam, Aneta Neumann, and Frank Neumann
• Abstract summary: We introduce a bi-level evolutionary algorithm to maximise the structural diversity of the set of solutions. We empirically determine the best method to obtain diversity. Our experimental results show a significant improvement of the QD approach in terms of structural diversity for most TTP benchmark instances.
• Score: 11.590506672325668
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: There has been a growing interest in the evolutionary computation community to compute a diverse set of high-quality solutions for a given optimisation problem. This can provide the practitioners with invaluable information about the solution space and robustness against imperfect modelling and minor problems' changes. It also enables the decision-makers to involve their interests and choose between various solutions. In this study, we investigate for the first time a prominent multi-component optimisation problem, namely the Traveling Thief Problem (TTP), in the context of evolutionary diversity optimisation. We introduce a bi-level evolutionary algorithm to maximise the structural diversity of the set of solutions. Moreover, we examine the inter-dependency among the components of the problem in terms of structural diversity and empirically determine the best method to obtain diversity. We also conduct a comprehensive experimental investigation to examine the introduced algorithm and compare the results to another recently introduced framework based on the use of Quality Diversity (QD). Our experimental results show a significant improvement of the QD approach in terms of structural diversity for most TTP benchmark instances.

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