scholarly journals A Parallel Tabu Search for the Large-scale Quadratic Assignment Problem

Author(s):  
Omar Abdelkafi ◽  
Bilel Derbel ◽  
Arnaud Liefooghe
2005 ◽  
Vol 9 (2) ◽  
pp. 149-168 ◽  
Author(s):  
A. Misevičius

In this paper, we present an improved hybrid optimization algorithm, which was applied to the hard combinatorial optimization problem, the quadratic assignment problem (QAP). This is an extended version of the earlier hybrid heuristic approach proposed by the author. The new algorithm is distinguished for the further exploitation of the idea of hybridization of the well‐known efficient heuristic algorithms, namely, simulated annealing (SA) and tabu search (TS). The important feature of our algorithm is the so‐called “cold restart mechanism”, which is used in order to avoid a possible “stagnation” of the search. This strategy resulted in very good solutions obtained during simulations with a number of the QAP instances (test data). These solutions show that the proposed algorithm outperforms both the “pure” SA/TS algorithms and the earlier author's combined SA and TS algorithm. Key words: hybrid optimization, simulated annealing, tabu search, quadratic assignment problem, simulation.


2014 ◽  
Vol 3 (3) ◽  
pp. 391-396 ◽  
Author(s):  
Mohamad Amin Kaviani ◽  
Mehdi Abbasi ◽  
Bentolhoda Rahpeyma ◽  
Mohamad Mehdi Yusefi

2002 ◽  
Vol 6 (3) ◽  
pp. 143-153 ◽  
Author(s):  
Zvi Drezner

We propose a new heuristic for the solution of the quadratic assignment problem. The heuristic combines ideas from tabu search and genetic algorithms. Run times are very short compared with other heuristic procedures. The heuristic performed very well on a set of test problems.


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