Abstract
This paper presents a multiobjective optimization algorithm for solving tri-objective optimization problems with objectives of very different scales. As a version of the Multiobjective Evolutionary Algorithm based on Decomposition (MOEA/D), it adopts the Normal Boundary Intersection (NBI) based Tchebycheff approach to decompose a multiobjective optimization problem into a number of single objective subproblems. Particular attention has been paid to set the weight vectors of these subproblems for handling disparately scaled objectives. We have applied our proposed algorithm to a traffic grooming problem in the telecommunication fields. We also propose to use an indirect encoding approach to handle this very complicated problem. Our experimental studies show that our proposed method is able to produce very promising results for this real-world telecommunication problem.
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