A Comparative Study of Meta-heuristic Algorithms for Solving Quadratic Assignment Problem

نویسندگان

  • Gamal Abd El-Nasser A. Said
  • Abeer M. Mahmoud
  • El-Sayed M. El-Horbaty
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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عنوان ژورنال:
  • CoRR

دوره abs/1407.4863  شماره 

صفحات  -

تاریخ انتشار 2014