Analysis of objectives relationships in multiobjective problems using trade-off region maps

Pinheiro, Rodrigo L.; Landa-Silva, Dario; Atkin, Jason

Abstract

Understanding the relationships between objectives in many-objective optimisation problems is desirable in order to develop more effective algorithms. We propose a techniquefor the analysis and visualisation of complex relationships between many (three or more) objectives. This technique looks at conflicting, harmonious and independent objectives relationships from different perspectives. To do that, it uses correlation, trade-off regions maps and scatter-plots in a four step approach. We apply the proposed technique to a set of instances of the well-known multiobjective multidimensional knapsack problem. The experimental results show that with the proposed technique we can identify local and complex relationships between objectives, trade-offs not derived from pairwise relationships, gaps in the fitness landscape, and regions of interest. Such information can be used to tailor the development of algorithms.

Citation

Pinheiro, R. L., Landa-Silva, D., & Atkin, J. Analysis of objectives relationships in multiobjective problems using trade-off region maps. Presented at Proceedings of the 2015 Genetic and Evolutionary Computation Conference (GECCO 2015)

• Conference Name: Proceedings of the 2015 Genetic and Evolutionary Computation Conference (GECCO 2015)
• End Date: Jul 15, 2015
• Publication Date: Jul 15, 2015
• Deposit Date: Jan 21, 2016
• Publicly Available Date: Jan 21, 2016
• Peer Reviewed: Peer Reviewed
• Keywords: multiobjective optimization, search landscape analysis, knapsack problem, personnel scheduling
• Public URL: https://nottingham-repository.worktribe.com/output/756950
• Publisher URL: http://dl.acm.org/citation.cfm?doid=2739480.2754721
• Additional Information: Published in: GECCO '15 : Proceedings of the 2015 Annual Conference on Genetic and Evolutionary Computation. New York : ACM, 2015. ISBN 9781450334723, pp. 735-742. doi: 10.1145/2739480.2754721