Comparing Genetic Algorithm and Variable Neighborhood Search Method for Solving Job Shop Problem
Comparing Genetic Algorithm and Variable Neighborhood Search Method for Solving Job Shop Problem

Author(s): Jana Vugdelija
Subject(s): Social Sciences
Published by: Udruženje ekonomista i menadžera Balkana
Keywords: Job Shop; Scheduling problem; Genetic algorithm; Variable neighborhood search; Heuristics
Summary/Abstract: Job Shop scheduling problem is one of the most complex and researched problems in the field of production planning. In this paper, two methods for solving Job Shop scheduling problem are presented and compared. The genetic algorithm and variable neighborhood search method were chosen and implemented in software for solving Job Shop problem. The paper first briefly presents Job Shop scheduling problem and then explains the development of solving software and implementation of selected solution methods. The results of using implemented genetic algorithm and variable neighborhood search method are presented on test instances with various dimensions. Solutions obtained using these two methods were put in comparison and analyzed, as well as compared with the optimal or bestknown solutions in the literature.

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