Effective heuristics and meta-heuristics for the quadratic assignment problem with tuned parameters and analytical comparisons

Quadratic assignment problem (qap) is a well-known problem in the facility location and layout. it belongs to the np-complete class. there are many heuristic and meta-heuristic methods, which are presented for qap in the literature. in this paper, we applied 2-opt, greedy 2-opt, 3-opt, greedy 3-opt, and vnz as heuristic methods and tabu search (ts), simulated annealing, and particle swarm optimization as meta-heuristic methods for the qap. this research is dedicated to compare the relative percentage deviation of these solution qualities from the best known solution which is introduced in qaplib. furthermore, a tuning method is applied for meta-heuristic parameters. results indicate that ts is the best in 31% of qaps, and the ifls method, which is in the literature, is the best in 58 % of qaps; these two methods are the same in 11% of test problems. also, ts has a better computational time among heuristic and meta-heuristic methods.