Recently, Particle Swarm Optimization (PSO) algorithm has exhibited good performance across a wide range of application problems. A quick review of the literature reveals that research for solving the Quadratic Assignment Problem (QAP) using PSO approach has not much been investigated. In this paper, we design a hybrid meta-heuristic fuzzy scheme, called as variable neighborhood fuzzy particle ...

In this study, we introduce a cooperative parallel tabu search algorithm (CPTS) for the quadratic assignment problem (QAP). The QAP is an NP-hard combinatorial optimization problem that is widely acknowledged to be computationally demanding. These characteristics make the QAP an ideal candidate for parallel solution techniques. CPTS is a cooperative parallel algorithm in which the processors ex...

The quadratic assignment problem (QAP) belongs to the class of NP -hard combinatorial optimization problems. Although it has been studied extensively over the past 35 years, problems of size n 15 still prove to be intractable. Since good lower bounds are necessary to solve larger problem instances, we discuss the class of eigenvalue bounds for QAP and extend previous results of these continuous...

This paper addresses the application of the principles of feedback and self-controlling software to the tabu search algorithm. We introduce two new reaction strategies for the tabu search algorithm. The first strategy treats the tabu search algorithm as a target system to be controlled and uses a control-theoretic approach to adjust the algorithm parameters that affect search intensification. T...

Hybrid genetic algorithms have recently become very popular metaheuristic methods (Beasley [6]). Most genetic algorithms produce offspring by mating parents and attempt to improve the population makeup by replacing existing population members with superior offspring. In contrast, hybrid genetic algorithms, sometimes called memetic algorithms (Moscato [28]), incorporate some heuristic improvemen...

We present the first linear formulation using distance variables (used previously for the Linear Arrangement Problem) to solve the Quadratic Assignment Problem (QAP). The model involves O(n2) variables. It has been stengthened by facets and valid inequalities, and numerically tested with QAPLIB instances whose distance matrices are given by the shortest paths in grid graphs. For all the instanc...

In this paper an improved tabu search (ITS) based approach is proposed for solving facility layout problem (FLP) which is formulated as quadratic assignment problem (QAP). ITS is an improved version of conventional tabu search technique which incorporates three levels viz. intensification, reconstruction, and solution acceptance. To evaluate the efficacy of the proposed ITS, it is tested for be...

Iterated local search (ILS) is a surprisingly simple but at the same time powerful metaheuristic for nding high quality approximate solutions for combinatorial optimization problems. ILS is based on the repeated application of a local search algorithm to initial solution which are obtained by mutations of previously found local optima | in most ILS algorithms these mutations are applied to the ...

This paper is concerned with solving GQAPs (generalized quadratic assignment problems) to optimality. In these problems, given M facilities and N locations, the facility space requirements, the location available space, the facility installation costs, the flows between facilities, and the distance costs between locations, one must assign each facility to exactly one location so that each locat...