Industrial Management Studies

Current Issue

By Issue

By Author

By Subject

Author Index

Keyword Index

About Journal

Aims and Scope

Publication Ethics

Indexing and Abstracting

Related Links

FAQ

Peer Review Process

Journal Metrics

News

Memorandum of Understanding between the Quarterly and the Iranian Management Sciences Association

Article Writing Guide

Files

Reviewer 1402

Reviewer 1401

Reviewer 1400

Consultants

Publons

A Mathematical Model for Dynamic Facility Layout Problem Considering Transportation Devices

Document Type : Research Paper

Authors

1 Ph.D. Candidate in Industrial Engineering, Department of Industrial Engineering, Faculty of Industrial and Mechanic Engineering, Islamic Azad University, Qazvin Branch, Qazvin, Iran

2 Associate Professor, Department of Industrial Engineering, Faculty of Industrial and Mechanic Engineering, Islamic Azad University, Qazvin Branch, Qazvin, Iran

3 Assistant Professor, Department of Industrial Engineering, Faculty of Industrial and Mechanic Engineering, Islamic Azad University, Qazvin Branch, Qazvin, Iran

4 Associate Professor, Department of Industrial Management, Shahid Beheshti University

Abstract

The aim of dynamic facility layout problem is to find the best layout for facilities at a multi period planning horizon so that the total cost of material handling and relocating the facilities is minimized. This paper developed a bi-objective mathematical model which is able to simultaneously minimize the material handling costs between facilities and the cost of rearrangement facilities and material handling time. Due to probabilistic characteristic of the transporters, such as the time of handling operation and existence of the failure, calculating the time required to carry the material using analytical relationships is impossible.
Therefore, this paper uses the simulation approach and artificial neural networks. In this approach, a lot of scenarios are generated by combining of various levels of variables. Each scenario shows the location of the facilities and how transportation operations in each period is performed. Then each of these scenarios is implemented through computer simulation and simulation results are considered as the response variable. Finally, using input and response variable, an artificial neural network is trained to accurately estimate the time of carrying out the transportation operations. Given that the above problem is a NP-hard; this paper proposes a new meta-heuristic algorithm to optimize the problem and compares the performance of the proposed algorithm with existing algorithms in literature.

Keywords

References
Aiello G., Enea M., Galante G., (2006), A multi-objective approach to facility layout problem by genetic search algorithm and Electre method, Robotics and Computer-Integrated Manufacturing 22,447–455.
Al Jadaan O., Rao C.R., Rajamani L., (2008), “Non-Dominated ranked genetic algorithm for solving Multi-Objective optimization problems: NRGA”, Journal of Theoretical and Applied Information Technology, 60-67.
Azevedo, M.M., Crispim, J.A., Pinho. J., (2017). A dynamic multi-objective approach for the reconfigurable multi-facility layout problem. Journal of Manufacturing Systems, 42,140-152.
Azimi P., Charmchi H.R., (2010), A new optimization via simulation approach for dynamic facility layout problem with budget constraints, Modelling and Simulation in Engineering 2012, 1-9.
Balakrishnan, J., Cheng, C.H., (1998). Dynamic layout algorithms: A state-of-the-art survey. Omega 26 (4), 507–521.
Baykasoglu A., Dereli T., Sabuncu, I., (2006), An ant colony algorithm for solving budget constrained and unconstrained dynamic facility layout problems, Omega 34(4), 385–396.
Baykasoglu, A., & Gindy, N. N. Z. (2001). A simulated annealing algorithm for dynamic facility layout problem. Computers and Operations Research, 28(14), 1403–1426.
Benjaafar, S., Heragu, S. S., & Irani, S. A. (2002). "Next generation factory layouts", Research challenges and recent progress. Interface, 32(6), 58–76.
Conway, D. G., & Venkataramanan, M. A. (1994). Genetic search and the dynamic facility layout problem. Computers and Operations Research, 21(8), 955– 960.
Deb, K., Agrawal, S., Pratap. A. and Meyarivan. T. (2000). A fast elitist non-dominated sorting genetic algorithm for multi-objective optimization: NSGA-II. IEEE Transactions on Evolutionary Computation, 6(2), 182-197
Deyi, L., Haijun, M., & Xuemei, S. (1995). Membership clouds and membership cloud generators, Computer Research and Development, 32(6), 15–20.
Dileep R. Sule, (2009), "Manufacturing Facilities, Locations, Planning and Design", 3rd Edition, CRC Press.
El-Baz M. Adel R., (2004), A genetic algorithm for facility layout problems of different manufacturing environments, Computers and Industrial Engineering 47,233–246
El-Rayes K., Said H., (2009), Dynamic site layout planning using approximate dynamic programming, Journal of Computing in Civil Engineering, 23(2), 119-127.
Guan J., Lin G., (2016), Hybridizing variable neighborhood search with ant colony optimization for solving the single row facility layout problem, European Journal of Operational Research 248 (3), 899–909.
Lacksonen, T.A. and Enscore, E.E (1993), Quadratic Assignment Algorithms for the Dynamic Layout Problem. International Journal of Production Research. Vol.31, No. 3, 503-517.
Lawrence M, Petterson A .1998. BrainMaker User’s Guide and Reference Manual, 7 th Edition. California Scientific Software, Nevada City, CA 95959
Marvin A.A., Sukran N.K., Basheer M.K., (2006), An empirical comparison of tabu search, simulated annealing, and genetic algorithms for facilities location problems, International Journal of Production Economies, 103, 742–754.
McKendall, A.R., Shang, J., Kuppusamy, S., (2006). Simulated annealing heuristics for the dynamic facility layout problem. Computers and Operations Research, 33 (8), 2431–2444.
Mir, M., Imam, M. H. (2001). A hybrid optimization approach for layout design of unequal-area facilities. Computers & Industrial Engineering, 39(1–2), 49–63.
Neghabi, H., Tari, F.G., (2016), A new concept of adjacency for concurrent consideration of economic and safety aspects in design of facility layout problems, Journal of Loss Prevention in the Process Industries 40, 603–614
           Paes, F.G., Pessoa, A.A., Vidal, T., (2017), A hybrid genetic algorithm with decomposition phases for the unequal Area Facility Layout Problem, European Journal of Operational Research 256 (3), 742–756.
           Rosenblatt MJ., (1986). The dynamics of plant layout. Management Science; 32(1):76–86.
           Samarghandi, H., Eshghi, K., (2010), An efficient tabu algorithm for the single row facility layout problem. European Journal of Operational Research 205:98–105.
           Tavakkoli-Moghaddam R., Shayan E., (1998), Facilities layout design by genetic algorithms, Computers and Industrial Engineering 35 (3-4) ,527-530.
           Tompkins, J. A. White, J. A. Bozer, Y. A. Frazelle, E. H., Tanchoco, J. M., Trevino, J (1996), "Facilities planning”, New York: Wiley.
           Ulutas B., Islier A., (2015), Dynamic facility layout problem in footwear industry, Journal of Manufacturing Systems 36, 55–61.
           Urban, T. L. (1993). A heuristic for the dynamic facility layout problem. IIE Transactions, 25(4), 57–63.
           Urban, T. L. (1998). Solution procedures for the dynamic facility layout problem. Annals of Operations Research, 76(1), 323–342.
           Wang, S., Zuoa, X., Liua, X., Zhaoc, X., Li, J., (2015), Solving dynamic double row layout problem via combining simulated annealing and mathematical programming, Applied Soft Computing 37, 303–310.
           Xu, J., Song, X., (2015), Multi-objective dynamic layout problem for temporary construction 4 facilities with unequal-area departments under fuzzy random, Knowledge-Based Systems 81, 30–45.
 
 
 
Industrial Management Studies
Volume 18, Issue 57
July 2020
Pages 43-99
Files
Share
How to cite
Statistics