A hybrid metaheuristic for multiobjective unconstrained binary quadratic programming

Abstract : The conventional Unconstrained Binary Quadratic Programming (UBQP) problem is known to be a unified modeling and solution framework for many combinatorial optimization problems. This paper extends the single-objective UBQP to the multiobjective case (mUBQP) where multiple objectives are to be optimized simultaneously. which combines an elitist evolutionary multiobjective optimization algorithm and a state-of-the-art single-objective tabu search procedure by using an achievement scalarizing function. Finally, we define a formal model to generate mUBQP instances and validate the performance of the proposed approach in obtaining competitive results on large-size mUBQP instances with two and three objectives.
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Applied Soft Computing, Elsevier, 2014, 16, pp.10-19. 〈10.1016/j.asoc.2013.11.008〉
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Arnaud Liefooghe, Sébastien Verel, Jin-Kao Hao. A hybrid metaheuristic for multiobjective unconstrained binary quadratic programming. Applied Soft Computing, Elsevier, 2014, 16, pp.10-19. 〈10.1016/j.asoc.2013.11.008〉. 〈hal-00801793v3〉

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