Document Type : Research Paper


1 Young Researchers and Elite Club, Arak Branch, Islamic Azad Univercity, Arak, Iran.

2 Department of Industrial Engineering, Islamic Azad University of Arak, Arak, Iran.


The Quadratic Assignment Problem (QAP) is one of the problems of combinatorial optimization belonging to the NP-hard problems’ class and has a wide application in the placement of facilities. Thus far, many efforts have been made to solve this problem and countless algorithms have been developed to achieve the optimal solutions; one of which is the Simulated Annealing (SA) algorithm. This paper aims at finding a suitable layout for the facilities of an industrial workshop by using a Developed Simulated Annealing (DSA) method.


Main Subjects

[1]     Koopmans, T. C., & Beckmann, M. (1957). Assignment problems and the location of economic activities. Econometrica: journal of the econometric society, 53-76.
[2]      Azadivir, F., & Wang, J. (2000). Dynamic facility layout design using simulation and genetic algorithms. International journal of production research, 38, 4369–4383.
[3]     Gupta, T., & Seifoddini, H. I. (1990). Production data based similarity coefficient for machine-component grouping decisions in the design of a cellular manufacturing system. The international journal of production research28(7), 1247-1269.
[4]     Afentakis, P., Millen, R. A., & Solomon, M. M. (1990). Integrated approach to facilities layout using expert systems. International journal of production research28(2), 311-323.
[5]     Mak, K. L., Wong, Y. S., & Chan, F. T. S. (1998). A genetic algorithm for facility layout problems. Computer integrated manufacturing systems11(1-2), 113-127.
[6]     Stützle, T. (2006). Iterated local search for the quadratic assignment problem. European journal of operational research174(3), 1519-1539.
[7]     Hicks, C. (2006). A Genetic Algorithm tool for optimising cellular or functional layouts in the capital goods industry. International journal of production economics104(2), 598-614.
[8]     Azadeh, A., & Izadbakhsh, H. R. (2008). A multi-variate/multi-attribute approach for plant layout design. International journal of industrial engineering: theory, applications and practice15(2), 143-154.
[9]     Gao, X., Zhou, Y., Amir, M. I. H., Rosyidah, F. A., & Lee, G. M. (2017). A hybrid genetic algorithm for multi-emergency medical service center location-allocation problem in disaster response. International journal of industrial engineering: theory, applications and practice, 6(24), 32-41.
[10] Golestaneh, R., Jafari, A., Khalilzadeh, M., & Karimi, H. (2013). Minimizing total resource tardiness penalty costs in the resource constrained project scheduling problem with metaheuristic algorithms. International journal of research in industrial engineering2(3), 47-57.
[11] Pichka, K., Ashjari, B., Ziaeifar, A., & Nickbeen, P. (2014). Open vehicle routing problem optimization under realistic assumptions. International journal of research3(2), 46-55.
[12] Moradi, N., & Shadrokh, S. (2019). A simulated annealing optimization algorithm for equal and un-equal area construction site layout problem. International journal of research in industrial engineering8(2), 89-104.
[13] Xia, Y. (2010). An efficient continuation method for quadratic assignment problems. Computers & operations research37(6), 1027-1032.
[14] Gary, M. R., & Johnson, D. S. (1979). Computers and intractability: a guide to the theory of np-completeness.
[15] Schmitt, L. M., Nehaniv, C. L., & Fujii, R. H. (1998). Linear analysis of genetic algorithms. Theoretical computer science200(1-2), 101-134.
[16] Černý, V. (1985). Thermodynamical approach to the traveling salesman problem: an efficient simulation algorithm. Journal of optimization theory and applications45(1), 41-51.
[17] Kirkpatrick, S., Gelatt, C. D., & Vecchi, M. P. (1983). Optimization by simulated annealing. Science220(4598), 671-680.
[18] Ohmori, S., Yoshimoto, K., & Ogawa, K. (2010, October). Solving facility layout problem-continuous simulated annealing. 2010 8th international conference on supply chain management and information (pp. 1-5). IEEE.