A Comparative Study of Meta-heuristic Algorithms for Solving Quadratic Assignment Problem
نویسندگان
چکیده
Quadratic Assignment Problem (QAP) is an NPhard combinatorial optimization problem, therefore, solving the QAP requires applying one or more of the meta-heuristic algorithms. This paper presents a comparative study between Meta-heuristic algorithms: Genetic Algorithm, Tabu Search, and Simulated annealing for solving a real-life (QAP) and analyze their performance in terms of both runtime efficiency and solution quality. The results show that Genetic Algorithm has a better solution quality while Tabu Search has a faster execution time in comparison with other Meta-heuristic algorithms for solving QAP. Keywords—Quadratic Assignment Problem (QAP); Genetic Algorithm (GA); Tabu Search (TS); Simulated Annealing (SA); Performance Analysis
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ورودعنوان ژورنال:
- CoRR
دوره abs/1407.4863 شماره
صفحات -
تاریخ انتشار 2014