In this paper, we propose an algorithm based on so-called ruin and recreate (R&R) principle. The R&R approach is conceptual simple but at the same time powerful meta-heuristic for combinatorial optimization problems. The main components of this method are a ruin (mutation) procedure and a recreate (improvement) procedure. We have applied the R&R principle based algorithm for a well-known combin...

Assigning facilities to locations is one of the important problems, which significantly is influence in transportation cost reduction. In this study, we solve quadratic assignment problem (QAP), using a meta-heuristic algorithm with deterministic tasks and equality in facilities and location number. It should be noted that any facility must be assign to only one location. In this paper, first o...

The quadratic assignment problem (QAP) is an NP-hard combinatorial optimization problem with a wide variety of applications. Biogeography-based optimization (BBO), a relatively new optimization technique based on the biogeography concept, uses the idea of migration strategy of species to derive algorithm for solving optimization problems. It has been shown that BBO provides performance on a par...

Local search based heuristics have been demonstrated to give very good results for approximately solve the Quadratic Assignment Problem (QAP). In this paper, following the works of Weinberger and Stadler, we introduce a parameter, called the ruggedness coeecient, which measures the ruggedness of the QAP landscape which is the union of a cost function and a neighborhood. We give an exact express...

Quadratic assignment problem (QAP) is a well-known problem in the facility location and layout. It belongs to the NP-complete class. There are many heuristic and meta-heuristic methods, which are presented for QAP in the literature. In this paper, we applied 2-opt, greedy 2-opt, 3-opt, greedy 3-opt, and VNZ as heuristic methods and tabu search (TS), simulated annealing, and particle swarm optim...

This application solves the quadratic assignment problem (QAP) [1]. In QAP, we are given l locations and l facilities and the task is to assign the facilities to the locations to minimize the cost. We chose QAP for the following reasons: First, problem sizes of QAPs in real life problems are relatively small compared with other problems in permutation domains such as the traveling salesman prob...

The quadratic assignment problem (QAP) was first proposed by Koopmans and Beckman [5] in the context of the plant location problem. Given n facilities, represented by the set F f1 fn , and n locations represented by the set L l1 ln , one must determine to which location each facility must be assigned. Let An n ai j be a matrix where ai j represents the flow between facilities fi and f j. Let Bn...

The paper presents a new powerful technique to linearize the quadratic assignment problem. There are so many techniques available in literature that used In all these linear formulations, both number of variables and constraints significantly increase. problem (QAP) is well-known whereby set facilities allocated locations such way cost function distance flow between facilities. this problem, co...

We study a generalization of the quadratic assignment problem (QAP) by allowing multiple equipments to be assigned at a single location as long as resources at the location permit. This problem arises in many real world applications such as facility location problem and logistics network design. We call the problem as the generalized quadratic assignment problem (GQAP) and show that this relaxa...

This paper presents a Particle Swarm Optimization (PSO) algorithm for the Quadratic Assignment Problem (QAP) implemented on OpenCL platform. Motivations to our work were twofold: firstly we wanted to develop a dedicated algorithm to solve the QAP showing both time and optimization performance, secondly we planned to check, if the capabilities offered by popular GPUs can be exploited to accelera...