Summary
The present chapter aims to serve as a brief introduction for the rest of the chapters in this volume. The main goal is to provide a general overview of multi-objective combinatorial optimization, including its main basic definitions and some notions regarding the incorporation of user’s preferences. Additionally, we also present short descriptions of some of the most popular multi-objective evolutionary algorithms in current use. Since performance assessment is a critical task in multi-objective optimization, we also present some performance indicators, as well as some discussion on statistical validation in a multi-objective optimization context. The aim of this chapter is not to be comprehensive, but simply to touch on the main fundamental topics that are required to understand the material that is presented in the rest of the book.
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Coello Coello, C.A., Dhaenens, C., Jourdan, L. (2010). Multi-Objective Combinatorial Optimization: Problematic and Context. In: Coello Coello, C.A., Dhaenens, C., Jourdan, L. (eds) Advances in Multi-Objective Nature Inspired Computing. Studies in Computational Intelligence, vol 272. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11218-8_1
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