Multistart Tabu Search and Diversification Strategies for the Quadratic Assignment Problem

2009 ◽  
Vol 39 (3) ◽  
pp. 579-596 ◽  
Author(s):  
Tabitha James ◽  
CÉsar Rego ◽  
Fred Glover
Keyword(s):  
Tabu Search ◽  
Assignment Problem ◽  
Quadratic Assignment Problem ◽  
Quadratic Assignment ◽  
Diversification Strategies

AN IMPROVED HYBRID OPTIMIZATION ALGORITHM FOR THE QUADRATIC ASSIGNMENT PROBLEM

2005 ◽  
Vol 9 (2) ◽  
pp. 149-168 ◽  
Author(s):  
A. Misevičius
Keyword(s):  
Simulated Annealing ◽  
Tabu Search ◽  
Optimization Algorithm ◽  
Assignment Problem ◽  
Optimization Problem ◽  
Heuristic Algorithms ◽  
Quadratic Assignment Problem ◽  
Hybrid Optimization ◽  
Quadratic Assignment ◽  
Hybrid Optimization Algorithm

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.

scholarly journals A hybrid Tabu search-simulated annealing method to solve quadratic assignment problem

2014 ◽  
Vol 3 (3) ◽  
pp. 391-396 ◽  
Author(s):  
Mohamad Amin Kaviani ◽  
Mehdi Abbasi ◽  
Bentolhoda Rahpeyma ◽  
Mohamad Mehdi Yusefi
Keyword(s):  
Simulated Annealing ◽  
Tabu Search ◽  
Assignment Problem ◽  
Quadratic Assignment Problem ◽  
Quadratic Assignment ◽  
Simulated Annealing Method ◽  
Annealing Method

scholarly journals A new heuristic for the quadratic assignment problem

2002 ◽  
Vol 6 (3) ◽  
pp. 143-153 ◽  
Author(s):  
Zvi Drezner
Keyword(s):  
Genetic Algorithms ◽  
Tabu Search ◽  
Assignment Problem ◽  
Quadratic Assignment Problem ◽  
Quadratic Assignment ◽  
Test Problems ◽  
Heuristic Procedures

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.

Path Relinking with Multi-Start Tabu Search for the Quadratic Assignment Problem

2013 ◽  
pp. 52-70
Author(s):  
Tabitha James ◽  
Cesar Rego
Keyword(s):  
Particle Swarm Optimization ◽  
Tabu Search ◽  
Assignment Problem ◽  
Search Algorithm ◽  
Quadratic Assignment Problem ◽  
Particle Swarm ◽  
Optimization Methods ◽  
Path Relinking ◽  
Quadratic Assignment ◽  
Swarm Optimization

This paper introduces a new path relinking algorithm for the well-known quadratic assignment problem (QAP) in combinatorial optimization. The QAP has attracted considerable attention in research because of its complexity and its applicability to many domains. The algorithm presented in this study employs path relinking as a solution combination method incorporating a multistart tabu search algorithm as an improvement method. The resulting algorithm has interesting similarities and contrasts with particle swarm optimization methods. Computational testing indicates that this algorithm produces results that rival the best QAP algorithms. The authors additionally conduct an analysis disclosing how different strategies prove more or less effective depending on the landscapes of the problems to which they are applied. This analysis lays a foundation for developing more effective future QAP algorithms, both for methods based on path relinking and tabu search, and for hybrids of such methods with related processes found in particle swarm optimization.

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