a modified method to determine a well-dispersed subset of non-dominated vectors of an momilp problem
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abstract
this paper uses the l1−norm and the concept of the non-dominated vector, topropose a method to find a well-dispersed subset of non-dominated (wdsnd) vectorsof a multi-objective mixed integer linear programming (momilp) problem.the proposed method generalizes the proposed approach by tohidi and razavyan[tohidi g., s. razavyan (2014), determining a well-dispersed subset of non-dominatedvectors of multi-objective integer linear programming problem, international journalof industrial mathematics, (accepted for publication)] to find a wdsnd vectors of anmomilp problem.
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A MODIFIED METHOD TO DETERMINE A WELL-DISPERSED SUBSET OF NON-DOMINATED VECTORS OF AN MOMILP PROBLEM
This paper uses the L1−norm and the concept of the non-dominated vector, topropose a method to find a well-dispersed subset of non-dominated (WDSND) vectorsof a multi-objective mixed integer linear programming (MOMILP) problem.The proposed method generalizes the proposed approach by Tohidi and Razavyan[Tohidi G., S. Razavyan (2014), determining a well-dispersed subset of non-dominatedvectors of...
full textA new method to determine a well-dispersed subsets of non-dominated vectors for MOMILP problem
Multi-objective optimization is the simultaneous consideration of two or more objective functions that are completely or partially inconflict with each other. The optimality of such optimizations is largely defined through the Pareto optimality. Multiple objective integer linear programs (MOILP) are special cases of multiple criteria decision making problems. Numerous algorithms have been desig...
full texta new method to determine a well-dispersed subsets of non-dominated vectors for momilp problem
multi-objective optimization is the simultaneous consideration of two or more objective functions that are completely or partially inconflict with each other. the optimality of such optimizations is largely defined through the pareto optimality. multiple objective integer linear programs (moilp) are special cases of multiple criteria decision making problems. numerous algorithms have been desig...
full textA new method to determine a well-dispersed subsets of non-dominated vectors for MOMILP problem
Multi-objective optimization is the simultaneous consideration of two or more objective functions that are completely or partially in conflict with each other. The optimality of such optimizations is largely defined through the Pareto optimality. Multiple objective integer linear programs (MOILP) are special cases of multiple criteria decision making problems. Numerous algorithms have been desi...
full textWell-dispersed subsets of non-dominated solutions for MOMILP problem
This paper uses the weighted L$_1-$norm to propose an algorithm for finding a well-dispersed subset of non-dominated solutions of multiple objective mixed integer linear programming problem. When all variables are integer it finds the whole set of efficient solutions. In each iteration of the proposed method only a mixed integer linear programming problem is solved and its optimal solutions gen...
full textwell-dispersed subsets of non-dominated solutions for momilp problem
this paper uses the weighted l$_1-$norm to propose an algorithm for finding a well-dispersed subset of non-dominated solutions of multiple objective mixed integer linear programming problem. when all variables are integer it finds the whole set of efficient solutions. in each iteration of the proposed method only a mixed integer linear programming problem is solved and its optimal solutions gen...
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Journal title:
international journal of mathematical modelling and computationsجلد ۵، شماره ۲ (SPRING)، صفحات ۱۴۱-۱۴۷
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