A new method to determine a well-dispersed subsets of non-dominated vectors for MOMILP problem
Winter 2015, Volume 7 - Number 1 (9 صفحه - از 25 تا 33)
Multi-objective optimization is the simultaneous consideration of two or more objective functions thatare completely or partially in con ict with each other. The optimality of such optimizations is largelyde ned through the Pareto optimality. Multiple objective integer linear programs (MOILP) are specialcases of multiple criteria decision making problems. Numerous algorithms have been designed to solveMOILP and multiple objective mixed integer linear programs. However, MOILP have not receivedthe algorithmic attention that continuous problems have. This paper uses the data envelopmentanalysis (DEA) technique to nd a well-dispersed non-dominated vectors of multiple objective mixedinteger linear programming (MOMILP) problem with bounded or unbounded feasible region, whilethe previous methods consider only problems with bounded feasible region. To this end, it uses theL1norm and the modi ed slack-based measure (MSBM) model. The proposed method does notneed the ltering procedures and it ranks the elements of well-dispersed non-dominated vectors ofMOMILP problem. The proposed algorithm is illustrated by using two numerical examples.
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