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Assignment Problems

• ISBN-10 0898716632
• ISBN-13 978-0898716634
• Publisher Society for Industrial and Applied Mathematics
• Publication date March 19, 2009
• Language English
• Dimensions 7.25 x 0.75 x 10.25 inches
• Print length 395 pages
• See all details

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• Publisher ‏ : ‎ Society for Industrial and Applied Mathematics (March 19, 2009)
• Language ‏ : ‎ English
• Hardcover ‏ : ‎ 395 pages
• ISBN-10 ‏ : ‎ 0898716632
• ISBN-13 ‏ : ‎ 978-0898716634
• Item Weight ‏ : ‎ 1.92 pounds
• Dimensions ‏ : ‎ 7.25 x 0.75 x 10.25 inches
• #903 in Linear Programming (Books)
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Rainer e. burkard.

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The Quadratic Assignment Problem

Related Papers

Encyclopedia of Optimization

Panos Pardalos

Panos M Pardalos

Abstract This paper aims at describing the state of the art on quadratic assignment problems (QAPs). It discusses the most important developments in all aspects of the QAP such as linearizations, QAP polyhedra, algorithms to solve the problem to optimality, heuristics, polynomially solvable special cases, and asymptotic behavior.

Güneş Erdoğan

The Quadratic Assignment Problem (QAP) is one of the hardest combinatorial optimization problems known. Exact solution attempts proposed for instances of size larger than 15 have been generally unsuccessful even though successful implementations have been reported on some test problems from the QAPLIB up to size 36. In this dissertation, we analyze the binary structure of the QAP and present new IP formulations. We focus on “flow-based” formulations, strengthen the formulations with valid inequalities, and report computational experience with a branch-and-cut algorithm. Next, we present new classes of instances of the QAP that can be completely or partially reduced to the Linear Assignment Problem and give procedures to check whether or not an instance is an element of one of these classes. We also identify classes of instances of the Koopmans-Beckmann form of the QAP that are solvable in polynomial time. Lastly, we present a strong lower bound based on Bender’s decomposition.

Cesar Beltran-Royo

Pesquisa Operacional

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We investigate the classical Gilmore-Lawler lower bound for the quadratic assignment problem. We provide evidence of the difficulty of improving the Gilmore-Lawler bound and develop new bounds by means of optimal reduction schemes. Computational results are reported indicating that the new lower bounds have advantages over previous bounds and can be used in a branch-and-bound type algorithm for the quadratic assignment problem.

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Assignment Problems

• Institute of Discrete Mathematics (5050)

Research output : Book/Report › Book

Treatment code (Nähere Zuordnung)

• Basic - Fundamental (Grundlagenforschung)
• Application
• Theoretical

T1 - Assignment Problems

AU - Burkard, Rainer

AU - Dell'Amico, Mauro

AU - Martello, Silvano

N1 - 382 Seiten

SN - 978-0-898716-63-4

BT - Assignment Problems

PB - SIAM - Society of Industrial and Applied Mathematics

CY - Philadelphia

Location Science pp 345–363 Cite as

The Quadratic Assignment Problem

• Zvi Drezner 4  
• First Online: 01 January 2015

4571 Accesses

9 Citations

The quadratic assignment problem is reviewed in this chapter. Weights between pairs of facilities and distances between the same number of locations are given. The problem is to find the assignment of facilities to locations that minimizes the weighted sum of distances. This problem is considered to be one of the most difficult combinatorial optimization problems. The construction of efficient solution algorithms (exact or heuristic) is challenging and has been extensively investigated by the communities working in Operations Research/Management Science, Industrial Engineering, or Computer Science. Examples of applications are given, the related layout problem is briefly described, exact and heuristic solution algorithms are reviewed, and a list of test problem instances and results are reported.

• Exact methods
• Metaheuristics
• Quadratic assignment

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Adams W, Guignard M, Hahn P, Hightower W (2007) A level-2 reformulation-linearization technique bound for the quadratic assignment problem. Eur J Oper Res 180:983–996

Google Scholar  

Ahuja R, Orlin J, Tiwari A (2000) A descent genetic algorithm for the quadratic assignment problem. Comput Oper Res 27:917–934

Amin S (1999) Simulated jumping. Ann Oper Res 84:23–38

Anstreicher K, Brixius N, Gaux JP, Linderoth J (2002) Solving large quadratic assignment problems on computational grids. Math Program 91:563–588

Anstreicher KM, Brixius NW (2001) A new bound for the quadratic assignment problem based on convex quadratic programming. Math Program 89:341–357

Armour GC, Buffa ES (1963) A heuristic algorithm and simulation approach to relative location of facilities. Manag Sci 9:294–309

Battiti R, Tecchiolli G (1994) The reactive tabu search. ORSA J Comput 6:126–140

Bos J (1993) Zoning in forest management: a quadratic assignment problem solved by simulated annealing. J Environ Manag 37:127–145

Buffa ES, Armour GC, Vollmann TE (1962) Allocating facilities with CRAFT. Harv Bus Rev 42:136–158

Burer S, Vandenbussche D (2006) Solving lift-and-project relaxations of binary integer programs. SIAM J Optimiz 16:726–750

Burkard R, Rendl F (1984) A thermodynamically motivated simulation procedure for combinatorial optimization problems. Eur J Oper Res 17:169–174

Burkard RE (1990) Locations with spatial interactions: the quadratic assignment problem. In: Mirchandani PB, Francis RL (eds) Discrete location theory. Wiley, New York, pp 387–437

Burkard RE, Cela E (1999) Linear assignment problems and extensions. In: Pardalos P, Du D-Z (eds) Handbook of combinatorial optimization. Springer, Dordrecht, pp 75–149

Burkard RE (2013) Quadratic assignment problems. In: Pardalos P, Du D-Z (eds) Handbook of combinatorial optimization, 2nd edn. Springer, New York, pp 2741–2814

Burkard RE, Offermann J (1977) Entwurf von schreibmaschinentastaturen mittels quadratischer zuordnungsprobleme. Math Method Oper Res 21:121–132

Cantú-Paz E (2001) Migration policies, selection pressure, and parallel evolutionary algorithms. J Heuristics 7:311–334

de Carvalho Jr SA, Rahmann S (2006) Microarray layout as a quadratic assignment problem. In: Huson D, Kohlbacher O, Lupas A, Nieselt K, Zell A (eds) Proceedings of the German conference on bioinformatics, vol 83. Gesellschaft für Informatik, Bonn, pp 11–20

Cela E (1998) The quadratic assignment problem: theory and algorithms. Kluwer Academic Publishers, Dordrecht

Connoly D (1990) An improved annealing scheme for the QAP. Eur J Oper Res 46:93–100

Cordeau JF, Gaudioso M, Laporte G, Moccia L (2006) A memetic heuristic for the generalized quadratic assignment problem. INFORMS J Comput 18:433–443

Coxeter HSM (1973) Regular polytopes. Dover Publications, New York

Cung VD, Mautor T, Michelon P, Tavares AI (1997) A scatter search based approach for the quadratic assignment problem. In: Proceedings of the IEEE international conference on evolutionary computation and evolutionary programming (ICEC’97), Indianapolis, pp 165–170

Dickey JW, Hopkins JW (1972) Campus building arrangement using topaz. Transp Res 6:59–68

Drezner T, Drezner Z (2005) Genetic algorithms: mimicking evolution and natural selection in optimization models. In: Bar-Cohen Y (ed) Biomimetics—biologically inspired technologies. CRC Press, Boca Raton, pp 157–175

Drezner T, Drezner Z (2006) Gender specific genetic algorithms. INFOR Inform Syst Oper Res 44:117–127

Drezner Z (1975) Problems in non-linear programming (the allocation problem). Ph.D. thesis, The Technion, Haifa

Drezner Z (1980) DISCON—a new method for the layout problem. Oper Res 28:1375–1384

Drezner Z (1987) A heuristic procedure for the layout of a large number of facilities. Manag Sci 33:907–915

Drezner Z (2002) A new heuristic for the quadratic assignment problem. J Appl Math Decis Sci 6:163–173

Drezner Z (2003) A new genetic algorithm for the quadratic assignment problem. INFORMS J Comput 15:320–330

Drezner Z (2005a) A distance based rule for removing population members in genetic algorithms. 4OR-Q J Oper Res 3:109–116

Drezner Z (2005b) The extended concentric tabu for the quadratic assignment problem. Eur J Oper Res 160:416–422

Drezner Z (2006) Finding a cluster of points and the grey pattern quadratic assignment problem. OR Spectr 28:417–436

Drezner Z (2008a) Extensive experiments with hybrid genetic algorithms for the solution of the quadratic assignment problem. Comput Oper Res 35:717–736

Drezner Z (2008b) Tabu search and hybrid genetic algorithms for quadratic assignment problems. In: Jaziri W (ed) Tabu search, in-tech, pp 89–108. Available free on: http://books.i-techonline.com

Drezner Z (2010) On the unboundedness of facility layout problems. Math Method Oper Res 72:205–216

Drezner Z, Marcoulides GA (2003) A distance-based selection of parents in genetic algorithms. In: Resende MGC, de Sousa JP (eds) Metaheuristics: computer decision-making. Kluwer Academic Publishers, Boston, pp 257–278

Drezner Z, Misevičius A (2013) Enhancing the performance of hybrid genetic algorithms by differential improvement. Comput Oper Res 40:1038–1046

Drezner Z, Suzuki A (2010) Covering continuous demand in the plane. J Oper Res Soc 61:878–881

Drezner Z, Zemel E (1992) Competitive location in the plane. Ann Oper Res 40:173–193

Drezner Z, Hahn PM, Taillard ÉD (2005) Recent advances for the quadratic assignment problem with special emphasis on instances that are difficult for meta-heuristic methods. Ann Oper Res 139:65–94

Drezner Z, Misevičius A, Palubeckis G (2014) Exact algorithms for the solution of the grey pattern quadratic assignment problem. In review

Duman E, Uysal M, Alkaya AF (2012) Migrating birds optimization: a new metaheuristic approach and its performance on quadratic assignment problem. Inform Sci 217:65–77

Elshafei AN (1977) Hospital layout as a quadratic assignment problem. Oper Res Q 28:167–179

Fischetti M, Monaci M, Salvagnin D (2012) Three ideas for the quadratic assignment problem. Oper Res 60:954–964

Fleurent C, Ferland J (1994) Genetic hybrids for the quadratic assignment problem. In: Pardalos P, Wolkowicz H (eds) Quadratic assignment and related problems, DIMACS series in discrete mathematics and theoretical computer science, vol 16. American Methematical Society, Providence, pp 173–187

Fox BR, McMahon MB (1991) Genetic operators for sequencing problems. In: Rawlins G (ed) Foundations of genetic algorithms. Morgan-Kaufmann, San Mateo, pp 284–300

Francis RL, McGinnis LF Jr, White JA (1992) Facility layout and location: an analytical approach, 2nd edn. Prentice Hall, Englewood Cliffs

Gambardella L, Taillard ÉD, Dorigo M (1999) Ant colonies for the quadratic assignment problem. J Oper Res Soc 50:167–176

Geoffrion AM, Graves GW (1976) Scheduling parallel production lines with changeover costs: practical application of a quadratic assignment/lp approa ch. Oper Res 24:595–610

Gilmore P (1962) Optimal and suboptimal algorithms for the quadratic assignment problem. J SIAM 10:305–313

Glover F (1977) Heuristics for integer programming using surrogate constraints. Decis Sci 8:156–166

Glover F (1986) Future paths for integer programming and links to artificial intelligence. Comput Oper Res 13:533–549

Glover F, Laguna M (1997) Tabu search. Kluwer Academic Publishers, Boston

Hahn P, Grant T (1998) Lower bounds for the quadratic assignment problem based upon a dual formulation. Oper Res 46:912–922

Hahn P, Krarup J (2001) A hospital facility problem finally solved. J Intell Manuf 12:487–496

Hahn PM, Kim BJ, Guignard M, Smith JM, Zhu YR (2008) An algorithm for the generalized quadratic assignment problem. Comput Optim Appl 40:351–372

Hahn PM, Zhu YR, Guignard M, Hightower WL, Saltzman MJ (2012) A level-3 reformulation-linearization technique-based bound for the quadratic assignment problem. INFORMS J Comput 24:202–209

Heffley DR (1977) Assigning runners to a relay team. In: Ladany SP, Machol RE (eds) Optimal strategies in sports. North-Holland, Amsterdam, pp 169–171

Hilbert D, Cohn-Vossen S (1956) Geometry and the imagination (english translation of Anschauliche Geometrie, 1932). Chelsea Publishing Company, New York

Hillier FS, Connors MM (1966) Quadratic assignment problem algorithms and the location of indivisible facilities. Manag Sci 13:42–57

Holland JH (1975) Adaptation in natural and artificial systems. University of Michigan Press, Ann Arbor

Koopmans TC, Beckmann MJ (1957) Assignment problems and the location of economic activities. Econometrica 25:53–76

Laporte G, Mercure H (1988) Balancing hydraulic turbine runners: a quadratic assignment problem. Eur J Oper Res 35:378–381

Lawler EL (1973) Optimal sequencing of a single machine subject to precedence constraints. Manag Sci 19:544–546

Lee CG, Ma Z (2005) The generalized quadratic assignment problem. Department of Mechanical and Industrial Engineering, University of Toronto, MIE OR Technical Reports (TR2005-01)

Li Y, Pardalos PM (1992) Generating quadratic assignment test problems with known optimal permutations. Comput Optim Appl 1:163–184

Li Y, Pardalos PM, Resende MGC (1994) A greedy randomized adaptive search procedure for the quadratic assignment problem. In: Pardalos PM, Wolkowicz H (eds) Quadratic assignment and related problems, DIMACS series in discrete mathematics and theoretical computer science, vol 16, American Mathematical Society, Providence, pp 237–261

Loiola EM, de Abreu NMM, Boaventura-Netto PO, Hahn P, Querido T (2007) A survey for the quadratic assignment problem. Eur J Oper Res 176:657–690

Love RF, Wong JY (1976) Solving quadratic assignment problems with rectangular distances and integer programming. Nav Res Logist Q 23:623–627

Misevičius A (2003) A modified simulated annealing algorithm for the quadratic assignment problem. Informatica 14:497–514

Misevičius A (2011) Generation of grey patterns using an improved genetic-evolutionary algorithm: some new results. Inf Technol Control 40:330–343

Misevičius A (2012) An implementation of the iterated tabu search algorithm for the quadratic assignment problem. OR Spectr 34:665–690

Misevičius A, Blonskis J (2005) Experiments with tabu search for random quadratic assignment problems. Inf Technol Control 34:237–244

Misevičius A, Guogis E (2012) Computational study of four genetic algorithm variants for solving the quadratic assignment problem. In: Skersys T, Butkienè R, Butleris R (eds) Communications in computer and information science (CCIS). Proceedings of 18th international conference on information and software technologies ICIST 2012, vol 319. Springer, Berlin, pp 24–37

Misevičius A, Tomkevičius A, Karbauskas J (2006) Stagnation-protected tabu search variants for unstructured quadratic assignment problems. Inf Technol Control 35:363–370

Misevičius A, Guogis E, Stanevičienè E (2013) Computational algorithmic generation of high-quality colour patterns. In: Skersys T, Butkienè R, Butleris R (eds) Communications in computer and information science (CCIS). Proceedings of 19th international conference in information and software technologies ICIST 2013. Springer, Berlin, pp 285–296

Misevičius A (2004) An improved hybrid genetic algorithm: new results for the quadratic assignment problem. Knowl-Based Syst 17:65–73

Misevičius A (2005) A tabu search algorithm for the quadratic assignment problem. Comput Optim Appl 30:95–111

Misevičius A (2008) Restart-based genetic algorithm for the quadratic assignment problem. In: Bramer M, Coenen F, Petridis M (eds) Research and development in intelligent systems. Proceedings of AI-2008, the 28th SGAI international conference on innovative techniques and applications of artificial intelligence. Springer, London, pp 91–104

Misevičius A, Rubliauskas D (2009) Testing of hybrid genetic algorithms for structured quadratic assignment problems. Informatica 20:255–272

Misevičius A, Rubliauskas D, Barkauskas V (2009) Some further experiments with the genetic algorithm for the quadratic assignment problem. Inf Technol Control 38:325–332

Nugent C, Vollman T, Ruml T (1968) An experimental comparison of techniques for the assignment of facilities to locations. Oper Res 16:150–173

Nyberg A, Westerlund T (2012) A new exact discrete linear reformulation of the quadratic assignment problem. Eur J Oper Res 220:314–319

Nyström M (1999) Solving certain large instances of the quadratic assignment problem: Steinberg’s examples. Technical report, California Institute of Technology. http://resolver.caltech.edu/CaltechCSTR:2001.010

Okabe A, Suzuki A (1987) Stability of spatial competition for a large number of firms on a bounded two-dimensional space. Environ Plann A 16:107–114

Oliveira CAS, Pardalos PM, Resende MGC (2004) GRASP with path-relinking for the quadratic assignment problem. In: Ribeiro CC, Martins SL (eds) Efficient and experimental algorithms. Springer, Berlin/Heidelberg, pp 237–261

Pierce JF, Crowston WB (1971) Tree-search algorithms for quadratic assignment problems. Nav Res Logist Q 18:1–36

Pierskalla WP (1967) The tri-substitution method for the three-dimensional assignment problem. CORS J 5:71–81

Pierskalla WP (1968) The multidimensional assignment problem. Oper Res 16:422–431

Ramakrishnan KG, Resende M, Ramachandran B, Pekny J (2002) Tight QAP bounds via linear programming. In: Pardalos PM, Migdalas A, Burkard R (eds) Combinatorial and global optimization. World Scientific Publishing, Singapore, pp 297–303

Rendl F (2002) The quadratic assignment problem. In: Drezner Z, Hamacher H (eds) Facility location: applications and theory. Springer, Berlin

Rendl F, Sotirov R (2007) Bounds for the quadratic assignment problem using the bundle method. Math Program 109:505–524

Resende M, Ramakrishnan K, Drezner Z (1995) Computational experiments with the lower bound for the quadratic assignment problem based on linear programming. Oper Res 43:781–791

Roupin F (2004) From linear to semidefinite programming: an algorithm to obtain semidefinite relaxations for bivalent quadratic problems. J Comb Optim 8:469–493

Sahni S, Gonzalez T (1976) P-complete approximation problems. J ACM 23:555–565

Schaffer JD, Caruana RA, Eshelman LJ (1989) A study of control parameters affecting online performance of genetic algorithms. In: Schaffer JD (ed) Proceedings of the 3rd international conference on genetic algorithms. Morgan Kaufmann, San Mateo, pp 51–60

Sherali HD, Adams WP (1990) A hierarchy of relaxations between the continuous and convex hull representations for zero-one programming problems. SIAM J Discret Math 3:411–430

Sherali HD, Adams WP (1998) A reformulation-linearization technique for solving discrete and continuous nonconvex problems. Springer, Berlin

Skorin-Kapov J (1990) Tabu search applied to the quadratic assignment problem. ORSA J Comput 2:33–45

Steinberg L (1961) The backboard wiring problem: a placement algorithm. SIAM Rev 3:37–50

Suzuki A, Drezner Z (1996) The p-center location problem in an area. Locat Sci 4:69–82

Suzuki A, Okabe A (1995) Using Voronoi diagrams. In: Drezner Z (ed) Facility location: a survey of applications and methods. Springer, New York, pp 103–118

Szabo PG, Markot M, Csendes T, Specht E (2007) New approaches to circle packing in a square: with program codes. Springer, New York

Taillard ÉD (1991) Robust tabu search for the quadratic assignment problem. Parallel Comput 17:443–455

Taillard ÉD (1995) Comparison of iterative searches for the quadratic assignment problem. Locat Sci 3:87–105

Taillard ÉD (1998) Fant: fast ant system. Technical report, Istituto Dalle Molle Di Studi Sull Intelligenza Artificiale, iDSIA Technical Report IDSIA-46-98

Taillard ÉD (2000) An introduction to ant systems. In: Laguna M, González-Velarde J (eds) Computing tools for modeling, optimization and simulation. Wiley, New York, pp 131–144

Talbi EG, Roux O, Fonlupt C, Robillard D (2001) Parallel ant colonies for the quadratic assignment problem. Futur Gener Comput Syst 17:441–449

Tate D, Smith A (1995) A genetic approach to the quadratic assignment problem. Comput Oper Res 22:73–83

Thonemann U, Bölte A (1994) An improved simulated annealing algorithm for the quadratic assignment problem. Technical report, working paper, School of Business, Department of Production and Operations Research, University of Paderborn, Germany

Wilhelm M, Ward T (1987) Solving quadratic assignment problems by simulated annealing. IIE Trans 19:107–119

Wu Y, Ji P (2008) Solving the quadratic assignment problems by a genetic algorithm with a new replacement strategy. Int J Comput Intell 4:225–229

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Drezner, Z. (2015). The Quadratic Assignment Problem. In: Laporte, G., Nickel, S., Saldanha da Gama, F. (eds) Location Science. Springer, Cham. https://doi.org/10.1007/978-3-319-13111-5_13

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