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Author: search.filters.author.Janjarassuk, UdomSubject: search.filters.subject.genetic algorithm

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    Product recommendation based on genetic algorithm
    (2019-07-01)
    Janjarassuk, Udom
    ;
    Puengrusme, Sudatip
    In this paper, we propose a product recommendation system based on genetic algorithm to find the best recommendation for a combination of products to the customers. The model evaluation relies on customer preferences and product requirements as well as feature ratings from the product experts. The system is tested by using a case study from recommendation of power unit selection for recording studio. Experimental results are provided.
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    A comparative study of mixed-integer linear programming and genetic algorithms for solving binary problems
    (2018-06-15)
    Kuendee, Punyisa
    ;
    Janjarassuk, Udom
    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.