An evolutionary approach for bilevel multi-objective problems

Deb, Kalyanmoy ; Sinha, Ankur (2009) An evolutionary approach for bilevel multi-objective problems Communications in Computer and Information Science, 35 . pp. 17-24. ISSN 1865-0929

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Evolutionary multi-objective optimization (EMO) algorithms have been extensively applied to find multiple near Pareto-optimal solutions over the past 15 years or so. However, EMO algorithms for solving bilevel multi-objective optimization problems have not received adequate attention yet. These problems appear in many applications in practice and involve two levels, each comprising of multiple conflicting objectives. These problems require every feasible upper-level solution to satisfy optimality of a lower-level optimization problem, thereby making them difficult to solve. In this paper, we discuss a recently proposed bilevel EMO procedure and show its working principle on a couple of test problems and on a business decision-making problem. This paper should motivate other EMO researchers to engage more into this important optimization task of practical importance.

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ID Code:81035
Deposited On:03 Feb 2012 11:44
Last Modified:03 Feb 2012 11:44

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