A comparison of memetic algorithms, tabu search, and ant colonies for the quadratic assignment problem

Author

Merz, P. ; Freisleben, Bernd

Author_Institution

Dept. of Electr. Eng. & Comput. Sci., Siegen Univ., Germany

Volume

3

fYear

1999

fDate

1999

Abstract

A memetic algorithm (MA), i.e. an evolutionary algorithm making use of local search, for the quadratic assignment problem is presented. A new recombination operator for realizing the approach is described, and the behavior of the MA is investigated on a set of problem instances containing between 25 and 100 facilities/locations. The results indicate that the proposed MA is able to produce high quality solutions quickly. A comparison of the MA with some of the currently best alternative approaches-reactive tabu search, robust tabu search and the fast ant colony system-demonstrates that the MA outperforms its competitors on all studied problem instances of practical interest

Keywords

evolutionary computation; heuristic programming; quadratic programming; search problems; MA; ant colonies; evolutionary algorithm; facilities/locations; fast ant colony system; high quality solutions; local search; memetic algorithms; problem instances; quadratic assignment problem; reactive tabu search; recombination operator; Ant colony optimization; Design optimization; Electronic mail; Evolutionary computation; Genetics; NP-hard problem; Neural networks; Robustness; Simulated annealing; Traveling salesman problems;

fLanguage

English

Publisher

ieee

Conference_Titel

Evolutionary Computation, 1999. CEC 99. Proceedings of the 1999 Congress on

Conference_Location

Washington, DC

Print_ISBN

0-7803-5536-9

Type

conf

DOI

10.1109/CEC.1999.785529

Filename

785529