Tabu search for nonlinear and parametric optimization (with links to genetic algorithms)
Discrete Applied Mathematics - Special volume: viewpoints on optimization
ACO algorithms for the quadratic assignment problem
New ideas in optimization
QAPLIB – A Quadratic Assignment ProblemLibrary
Journal of Global Optimization
A Template for Scatter Search and Path Relinking
AE '97 Selected Papers from the Third European Conference on Artificial Evolution
Scatter Search: Methodology and Implementations in C
Scatter Search: Methodology and Implementations in C
Advances in evolutionary computing
A tabu search algorithm for the quadratic assignment problem
Computational Optimization and Applications
Metaheuristic Optimization via Memory and Evolution: Tabu Search and Scatter Search (Operations Research/Computer Science Interfaces Series)
Parallel Path-Relinking Method for the Flow Shop Scheduling Problem
ICCS '08 Proceedings of the 8th international conference on Computational Science, Part I
Solving the flow shop problem by parallel programming
Journal of Parallel and Distributed Computing
Multistart tabu search and diversification strategies for the quadratic assignment problem
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Parallel scatter search algorithm for the flow shop sequencing problem
PPAM'07 Proceedings of the 7th international conference on Parallel processing and applied mathematics
Journal of Intelligent Manufacturing
Exploration and exploitation bias of crossover and path relinking for permutation problems
PPSN'06 Proceedings of the 9th international conference on Parallel Problem Solving from Nature
Path Relinking with Multi-Start Tabu Search for the Quadratic Assignment Problem
International Journal of Swarm Intelligence Research
Parallel tabu search algorithm for the hybrid flow shop problem
Computers and Industrial Engineering
Solving bi-objective flow shop problem with hybrid path relinking algorithm
Applied Soft Computing
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The quadratic assignment problem is a classical combinatorial optimization problem that has garnered much attention due to both its many applications and its solution complexity. Originally used to model a location problem in the 1950s, the QAP is computationally very difficult to solve, making it an ideal candidate for metaheuristic approaches. Path relinking is an evolutionary metaheuristic based on maintaining and exploiting search information by drawing on principles shared in common with tabu search. This article proposes and implements a design for both a sequential and a parallel path-relinking algorithm tailored for the QAP. To demonstrate the benefits of the parallelization, we tested both the sequential and parallel versions of the algorithm using problems from QAPLIB. In spite of the underlying PR method's simplicity, we obtain results that are competitive with some of the best outcomes in the literature.This article is part of a special issue on advanced heuristics in transportation and logistics.