Results 1  10
of
11
Solving Large Quadratic Assignment Problems on Computational Grids
, 2000
"... The quadratic assignment problem (QAP) is among the hardest combinatorial optimization problems. Some instances of size n = 30 have remained unsolved for decades. The solution of these problems requires both improvements in mathematical programming algorithms and the utilization of powerful computat ..."
Abstract

Cited by 82 (7 self)
 Add to MetaCart
The quadratic assignment problem (QAP) is among the hardest combinatorial optimization problems. Some instances of size n = 30 have remained unsolved for decades. The solution of these problems requires both improvements in mathematical programming algorithms and the utilization of powerful computational platforms. In this article we describe a novel approach to solve QAPs using a stateoftheart branchandbound algorithm running on a federation of geographically distributed resources known as a computational grid. Solution of QAPs of unprecedented complexity, including the nug30, kra30b, and tho30 instances, is reported.
The Steinberg Wiring Problem
, 2001
"... this paper was written we learned of a previously unreleased technical report by M. Nystrom [35] that describes the solution of the ste36b/c problems. Nystrom used a distributed B&B algorithm based on the GLB, implemented on 22 200 MHz Pentium Pro CPUs. The serial time to solve the ste36b/c inst ..."
Abstract

Cited by 5 (0 self)
 Add to MetaCart
(Show Context)
this paper was written we learned of a previously unreleased technical report by M. Nystrom [35] that describes the solution of the ste36b/c problems. Nystrom used a distributed B&B algorithm based on the GLB, implemented on 22 200 MHz Pentium Pro CPUs. The serial time to solve the ste36b/c instances on one of these CPUs is estimated to be approximately 60 days/200 days, respectively. (The time for ste36c is substantially higher because this problem was solved using an initial incumbent value of +1.) "wiring" 2001/12/19 page 13 i i i i i i i i 13 1.E+00 1.E+01 1.E+02 1.E+03 1.E+04 1.E+05 1.E+06 1.E+07 1.E+08 0 3 6 9 12 15 18 21 24 27 30 33 Level Figure 4. Distribution of nodes in solution of ste36a 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0 3 6 9 12 15 18 21 24 27 30 33 Level 0.0 20.0 40.0 60.0 80.0 100.0 120.0 140.0 160.0 180.0 200.0 Rel. Gap Cum. Hrs
The MultiStory Space Assignment Problem
, 2008
"... ... (MSAP) is an innovative formulation of the multistory facility assignment problem that allows one to model the location of departments of unequal size within multistory facilities as a Generalized Quadratic 3dimensional Assignment Problem (GQ3AP). Not only can the MSAP generate the design of ..."
Abstract

Cited by 4 (2 self)
 Add to MetaCart
... (MSAP) is an innovative formulation of the multistory facility assignment problem that allows one to model the location of departments of unequal size within multistory facilities as a Generalized Quadratic 3dimensional Assignment Problem (GQ3AP). Not only can the MSAP generate the design of the location of the departments in the facility, the MSAP also includes the evacuation planning for the facility. The formulation, background mathematical development, and computational experience with a branch and bound algorithm for the MSAP are also presented.
unknown title
"... A generalization of the MDS method by mixed integer linear and nonlinear mathematical models ..."
Abstract
 Add to MetaCart
(Show Context)
A generalization of the MDS method by mixed integer linear and nonlinear mathematical models
A hierarchical facility layout planning approach for large and complex hospitals
"... Abstract The transportation processes for patients, personnel, and material in large and complex maximumcare hospitals with many departments can consume significant resources and thus induce substantial logistics costs. These costs are largely determined by the allocation of the different departme ..."
Abstract
 Add to MetaCart
(Show Context)
Abstract The transportation processes for patients, personnel, and material in large and complex maximumcare hospitals with many departments can consume significant resources and thus induce substantial logistics costs. These costs are largely determined by the allocation of the different departments and wards in possibly multiple connected hospital buildings. We develop a hierarchical layout planning approach based on an analysis of organizational and operational data from the Hannover Medical School, a large and complex university hospital in Hannover, Germany. The purpose of this approach is to propose locations for departments and wards for a given system of buildings such that the consumption of resources due to those transportation processes is minimized. We apply the approach to this realworld organizational and operational dataset as well as to a fictitious hospital building and analyze the algorithmic behavior and resulting layout.
A BiogeographyBased Optimization Algorithm Hybridized with Tabu Search for the Quadratic Assignment Problem
"... The quadratic assignment problem (QAP) is an NPhard combinatorial optimization problem with a wide variety of applications. Biogeographybased optimization (BBO), a relatively new optimization technique based on the biogeography concept, uses the idea of migration strategy of species to derive alg ..."
Abstract
 Add to MetaCart
(Show Context)
The quadratic assignment problem (QAP) is an NPhard combinatorial optimization problem with a wide variety of applications. Biogeographybased 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 with other optimization methods. A classical BBO algorithm employs the mutation operator as its diversification strategy. However, this process will often ruin the quality of solutions in QAP. In this paper, we propose a hybrid technique to overcome the weakness of classical BBO algorithm to solve QAP, by replacing the mutation operator with a tabu search procedure. Our experiments using the benchmark instances from QAPLIB show that the proposed hybrid method is able to find good solutions for them within reasonable computational times. Out of 61 benchmark instances tested, the proposed method is able to obtain the best known solutions for 57 of them.
Solving Large Quadratic Assignment Problems on Computational Grids
"... The quadratic assignment problem (QAP) is among the hardest combinatorial optimization problems. Some instances of sizeÂ£Â¥ Â¤ 30 have remained unsolved for decades. The solution of these problems requires both improvements in mathematical programming algorithms and the utilization of powerful compu ..."
Abstract
 Add to MetaCart
(Show Context)
The quadratic assignment problem (QAP) is among the hardest combinatorial optimization problems. Some instances of sizeÂ£Â¥ Â¤ 30 have remained unsolved for decades. The solution of these problems requires both improvements in mathematical programming algorithms and the utilization of powerful computational platforms. In this article we describe a novel approach to solve QAPs using a stateoftheart branchandbound algorithm running on a federation of geographically distributed resources known as a computational grid. Solution of QAPs of unprecedented complexity, including the nug30, kra30b, and tho30 instances, is reported.
Solving Quadratic Assignment Problem on Cluster with a Bound of Reformulation Linearization Techniques
"... Abstract In this paper ¤, we propose an parallel branchandbound algorithm for the quadratic assignment problem based upon an efficient lower bound calculation developed by Hahn and Grant. The sequential version is very easy to achieve with the Bob++ library and the results are very encouraging. Fo ..."
Abstract
 Add to MetaCart
(Show Context)
Abstract In this paper ¤, we propose an parallel branchandbound algorithm for the quadratic assignment problem based upon an efficient lower bound calculation developed by Hahn and Grant. The sequential version is very easy to achieve with the Bob++ library and the results are very encouraging. For the parallel implementation of our algorithm, we ported our Bob++ library to the high level grid programming and runtime environment Athapascan. The performances obtaining with this algorithm running on one cluster for some instances of qap ¨ (size 25) are competitive.
Research Article A BiogeographyBased Optimization Algorithm Hybridized with Tabu Search for the Quadratic Assignment Problem
, 2015
"... Copyright © 2016 Wee Loon Lim et al.This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The quadratic assignment problem (QAP) is an NPh ..."
Abstract
 Add to MetaCart
(Show Context)
Copyright © 2016 Wee Loon Lim et al.This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The quadratic assignment problem (QAP) is an NPhard combinatorial optimization problem with a wide variety of applications. Biogeographybased 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 with other optimization methods. A classical BBO algorithm employs the mutation operator as its diversification strategy. However, this process will often ruin the quality of solutions in QAP. In this paper, we propose a hybrid technique to overcome the weakness of classical BBO algorithm to solve QAP, by replacing themutation operator with a tabu search procedure. Our experiments using the benchmark instances from QAPLIB show that the proposed hybrid method is able to find good solutions for them within reasonable computational times. Out of 61 benchmark instances tested, the proposed method is able to obtain the best known solutions for 57 of them. 1.