Solving Bilevel Multi-Objective Optimization Problems Using Evolutionary Algorithms

Abstract. Bilevel optimization problems require every feasible upperlevel solution to satisfy optimality of a lower-level optimization problem. These problems commonly appear in many practical problem solving tasks including optimal control, process optimization, game-playing strategy development, transportation problems, and others. In the context of a bilevel single objective problem, there exists a number of theoretical, numerical, and evolutionary optimization results. However, there does not exist too many studies in the context of having multiple objectives in each level of a bilevel optimization problem. In this paper, we address bilevel multi-objective optimization issues and propose a viable algorithm based on evolutionary multi-objective optimization (EMO) principles. Proof-of-principle simulation results bring out the challenges in solving such problems and demonstrate the viability of the proposed EMO technique for solving such problems. This paper scratches the surface of ...

• Type: Conference
• Year: 2009
• Where: EMO
• Authors: Kalyanmoy Deb, Ankur Sinha
• Keywords: Artificial Intelligence, Bilevel Optimization Problem, EMO 2009, Multi-objective Optimization, Optimization Problems