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A comparative study of mixed-integer linear programming and genetic algorithms for solving binary problems

Author(s)
Kuendee, Punyisa
Janjarassuk, Udom
Date Issued
June 15, 2018
Type
Conference Paper
DOI
10.1109/IEA.2018.8387111
Abstract
This paper aims to investigate the capability of mixed-integer linear programming (MILP) method and genetic algorithm (GA) to solve binary problem (BP). A comparative study on the MILP method and GA with default and tuned setting to find out an optimal solution is presented. The mixed-integer programming library (MIPLIB 2010) is used to test and evaluate algorithms. The evaluation is shown in quality of the solution and the execution time of computation. The results show that GA is superior to MILP in execution time with inconsistent results. However, MILP is superior to GA in quality of the solution with more stable results.
Citation
2018 5th International Conference on Industrial Engineering and Applications Iciea 2018, 284-288, 2018
Subjects

binary problem

genetic algorithm

mixed integer program...

mixed-integer linear ...

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