Paper Info
Title
Evolutionary Diversity Optimisation for The Traveling Thief Problem
Abstract
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.rst 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 signi.cant improvement of the QD approach in terms of structural diversity for most TTP benchmark instances.
Year
DOI
Venue
2022
10.1145/3512290.3528862
PROCEEDINGS OF THE 2022 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE (GECCO'22)
Keywords
DocType
Citations 
Evolutionary diversity optimisation, multi-component optimisation, problems, traveling thief problem
Conference
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Adel Nikfarjam102.37
Aneta Neumann200.68
Frank Neumann304.06