A theoretical fundation metaheuristic method to solve some multiobjective optimization problems

 
 
 
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  • Abstract


    In the literature, many metaheuristics are available to find a good approximation of efficient solutions of optimization problems. But most of these methods don't have a theoretical foundation. In this work, we propose the theoretical foundation of MOMA (Multi-Objectif Alienor Metaheuristic) method and moreover its efficiency to solve linear optimization problems. This method is the combination of multiobjectif concepts and the Alienor transformation, which allows to transform a multiobjectif optimization problem in optimization of a single variable function. We solve two didactic examples in order to allow the best presentation of the MOMA method and besides the quality of obtained solutions is proved.


  • Keywords


    metaheuristics, Alienor transformation, linear multiobjectif optimization, weighted Tchebychev metric, Pareto optimality.

 

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Article ID: 902
 
DOI: 10.14419/ijamr.v2i4.902




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