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Multi-objective Optimization

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Abstract

Multi-objective optimization is an integral part of optimization activities and has a tremendous practical importance, since almost all real-world optimization problems are ideally suited to be modeled using multiple conflicting objectives. The classical means of solving such problems were primarily focused on scalarizing multiple objectives into a single objective, whereas the evolutionary means have been to solve a multi-objective optimization problem as it is. In this chapter, we discuss the fundamental principles of multi-objective optimization, the differences between multi-objective optimization and single-objective optimization, and describe a few well-known classical and evolutionary algorithms for multi-objective optimization. Two application case studies reveal the importance of multi-objective optimization in practice. A number of research challenges are then highlighted. The chapter concludes by suggesting a few tricks of the trade and mentioning some key resources to the field of multi-objective optimization.

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Authors and Affiliations

  1. Department of Electrical and Computer Engineering, Michigan State University, East Lansing, 428 S. Shaw Lane, 2120 EB, MI, 48824, USA

    Kalyanmoy Deb (Koenig Endowed Chair Professor) & Kalyanmoy Deb (Professor)

  2. Department of Computer Science, Michigan State University, East Lansing, MI, USA

    Kalyanmoy Deb (Koenig Endowed Chair Professor) & Kalyanmoy Deb (Professor)

  3. Department of Mechanical Engineering, Michigan State University, East Lansing, MI, USA

    Kalyanmoy Deb (Koenig Endowed Chair Professor) & Kalyanmoy Deb (Professor)

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  1. Kalyanmoy Deb
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Editors and Affiliations

  1. Computing Science and Mathematics, University of Stirling, Scotland, United Kingdom

    Edmund K. Burke

  2. Research and Knowledge Transfer, University of Nottingham, Malaysia & UK, Semenyih, Malaysia

    Graham Kendall

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Deb, K., Deb, K. (2014). Multi-objective Optimization. In: Burke, E., Kendall, G. (eds) Search Methodologies. Springer, Boston, MA. https://doi.org/10.1007/978-1-4614-6940-7_15

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