The Effects of Memes on Memetic Algorithms for Solving Quadratic Assignment Problem

The quadratic assignment problem (QAP) is known as one of NP-hard combinatorial optimization problems where a set of facilities must be assigned to a set of locations in order to minimize total cost. In this paper, we present the effect of local search algorithm referred to as meme on Memetic Algorithms (MAs). We also compare four different local search metaheuristics: Hill Climbing Algorithm (HC), Tabu Search (TS), Simulated Annealing (SA), and Iterated Local Search (ILS) for solving QAP and analyze their performance in terms of solution quality. The results show that ILS is the best metaheuristic followed by SA, TS, and HC, respectively. While the MA using ILS as a meme is the best among all four MAs, the MA using SA as a meme is not the second-best metaheuristic, but the worst among all.