Genetic Hybrids for the Quadratic Assignment Problem

  title={Genetic Hybrids for the Quadratic Assignment Problem},
  author={Charles Fleurent and Jacques A. Ferland},
  booktitle={Quadratic Assignment and Related Problems},
A new hybrid procedure that combines genetic operators to existing heuristics is proposed to solve the Quadratic Assignment Problem (QAP). Genetic operators are found to improve the performance of both local search and tabu search. Some guidelines are also given to design good hybrid schemes. These hybrid algorithms are then used to improve on the best known solutions of many test problems in the literature. 
Highly Influential
This paper has highly influenced 13 other papers. REVIEW HIGHLY INFLUENTIAL CITATIONS

From This Paper

Topics from this paper.


Publications citing this paper.
Showing 1-10 of 146 extracted citations

Constrained neural approaches to quadratic assignment problems

Neural Networks • 1998
View 9 Excerpts
Highly Influenced

Extensions to Guided Local Search

View 4 Excerpts
Highly Influenced


Publications referenced by this paper.
Showing 1-9 of 9 references

A thermodynamically motivated simulation procedure for combinatorial optimization problems

R. E. Burkard, F. Rendl
European Journal of Operational Research • 1984
View 6 Excerpts
Highly Influenced

Improving search in genetic algorithms, Genetic Algorithms and Simulated Annealing

L. Booker
View 3 Excerpts

deWerra , Using tabu search techniques for graph coloring

A. Hertz, D.
Computing • 1987

Computer solutions of the traveling salesman problem

T. E. Vollmann
Bell System TechnicalJournal • 1965

Optimal and suboptimal algorithms for the quadratic assignment problem

P. C. Gilmore
SIAM Journal on Applied Mathematics • 1962

Rendl , A thermodynamically motivated simulation procedurefor combinatorial optimization problems

European Journal of Operational Research

Similar Papers

Loading similar papers…