- Azadeh, S., Haghighi, S. M., & Asadzadeh, S. M. (2014). A novel algorithm for layout optimization of injection process with random demands and sequence dependent setup times. Journal of Manufacturing Systems, 33, 287–302.
- Azar, A., & Abbasi, H. (2011). Designing a mathematical model of flexibility manufacturing system. Journal of Industrial Management Perspective, 4, 65-79. (In Persian).
- Balakrishnan, J., & Cheng, C. H. (1998). Dynamic layout algorithms: A state-of-the-art survey International Journal of Management Science 26(4), 507–521.
- Balakrishnan, J., Jacobs, F. R., & Venkataramanan, M. A. (1992). Solutions for the constrained dynamic facility layout problem. European Journal of Operational Research, 57, 280–286.
- Bashiri, M. & Karimi, H. (2015). The application of heuristic and meta-heuristic algorithms in industrial systems design using Matlab software. Shahed University Press. (In Persian).
- Benjaafar, S., & Sheikhzadeh, S. (2000). Design of flexible plant layouts. IIE Transactions, 32, 309-322.
- Braglia, M., Zanoni, S., & Zavanella, L. (2003). Layout design in dynamic environments: analytical issues. International Transition in Operation Research, 12, 1-19.
- Derakhshan Asl, A., & Kuan, K. Y. (2015). Solving unequal-area static and dynamic facility layout problems using modified particle swarm optimization. Journal of Intelligent Manufacturing, 28, 1317–1336.
- Drira, A., Pierreval, H., & Hajri-Gabouj, S. (2007). Facility layout problems: A survey. Annual Reviews in Control, 31, 255–267.
10. Eslaminia, A., & Azimi, P. (2020). Solving the Electric Vehicle Routing Problem Considering the Vehicle Volume Limitation Using a Simulated Annealing Algorithm. Journal of Industrial Management Perspective, 36, 165-188. (In Persian).
11. Fazlelahi, F. Z., Pournader, M., Gharakhani, M., & Sadjadi. (2015). A robust approach to design a single facility layout plan in dynamic manufacturing environments using a permutation-based genetic algorithm. Journal of Engineering Manufacture, 230(12), 2264-2274.
12. Forghani, K., Mohammadi, M., & Ghezavati, V. (2013). Designing robust layout in cellular manufacturing systems with uncertain demands. International Journal of Industrial Engineering Computations, 4(2), 215-226.
13. Groover, M. P. (2008). Automation, production systems, and Computer-Integrated manufacturing. New Jersey: Pearson Education Inc.
14. Ghadirpour, S. M., Rahmani, D., Moslemipour, G. (2020). Routing flexibility for unequal–area stochastic dynamic facility layout problem in flexible manufacturing systems. International Journal of Industrial Engineering & Production Research, 31(2), 269-285.
15. Jithavech, I., & Krishnan, K. (2010). A simulation-based approach for risk assessment of facility layout designs under stochastic product demands. International Journal of Advanced Manufaturing Technology, 49, 27-40.
16. Krishnan, K. K., Cheraghi, S. H., & Nayak, C. N. (2006). Dynamic From-Between Chart: a new tool for solving dynamic facility layout problems. International Journal of Industrial and Systems Engineering, 1(1/2), 182-200.
17. Krishnan, K. K., Cheraghi, S., & Nayak, C. (2008). Dynamic facility layout design for multiple production scenarios in a dynamic environment. International Journal of Industrial and Systems Engineering, 3(2), 105-133.
18. Kirkpatrick, S., & al, e. (1983). Optimization by Simulated Annealing. Science, 220(4598), 671-680.
19. Lee, H. Y., Kang, S., & Chae, J. (2015). Mutation effects in a genetic algorithm for a facility layout problem in QAP form. International Journal of Advanced Logistics, 4(3), 170-179.
20. Lee, T. S., Moslemipour, G., Ting, T. O., & Rilling, D. (2012). A Novel Hybrid ACO/SA Approach to Solve Stochastic Dynamic Facility Layout Problem (SDFLP). Communication in Computer and Information Science, special issue: Emerging Intelligent Computing Technology and Applications, 304, 100-108.
21. Lee, T., Moslemipour, G., (2012). Intelligent design of a flexible cell layout with maximum stability in a stochastic dynamic situation. Trends in intelligent robotics, automation, and manufacturing. Springer, 398-405.
22. Misevicius, A. (2003). A modified simulated annealing algorithm for quadratic assignment problem. Informatica, 14, 497-514.
23. Montreuil, B., & LaForge, A. (1992). Dynamic layout design given a scenario tree of probable futures. European Journal of Operational Research, 63(2), 271-286.
24. Moslemipour, G. (2017).Robust inter and intra-cell layouts design model dealing with stochastic dynamic problems. Journal of Industrial and Systems Engineering, 10(4), 123-40.
25. Moslemipour, G. (2016). Dynamic intracellular layout design using simulated annealing algorithm in random environment of cellular manufacturing systems. National Conference of decision making in engineering and management. Aliabad Katool. COI in civilica: EMDM01_100. (In Persian).
26. Moslemipour, G., Lee, T. S. (2012). Intelligent design of a dynamic machine layout in uncertain environment of flexible manufacturing systems. International Journal of Flexibility Manufacturing System, 1849-1860.
27. Moslemipour, G., Lee, T. S., & Rilling, D. (2012). A review of intelligent approaches for designing dynamic and robust layouts in flexible manufacturing systems. International Journal of Advanced Manufaturing Technology, 60, 11-27.
28. Moslemipour, G., Lee, T. S., & Loong, Y.T. (2018).Solving stochastic dynamic facility layout problems using proposed hybrid AC-CS-SA meta-heuristic algorithm.Int. J. Industrial and Systems Engineering, 28(1), 1-31.
29. Nematian, J. (2014). A robust single row facility layout problem with fuzzy random variables. International Journal of Advanced Manufaturing Technology, 72, 255–267.
30. Palekar US et al. (1992). Modeling uncertainties in plant layout problems. European Journal of Operational Research, 63, 347-359.
31. Pourvaziri, H., & Naderib, B. (2014). A hybrid multi-population genetic algorithm for the dynamic facility layout problem. Applied Soft Computing, 24, 457–469.
32. Sahni, S., & Gonzalez, T. (1976). P-complete approximation problem. Journal of the ACM, 23(3), 555-565.
33. Vitayasak, S., Pongcharoen, P., & Hicks, C. (2019). Robust machine layout design under dynamic environment: Dynamic customer demand and machine maintenance.Expert Systems with Applications, doi.org/10.1016/j.eswax.2019.10 0 015.
34. Sheikh, R., & Shambiati, H. (2016). Facility Location Problem in uncertainty conditions based on D numbers. Journal of Industrial Management Perspective, 20, 143-166. (In Persian).
35. Suman, B., & Kumar, P. (2006). A Survey of simulated annealing as a tool for single and multiobjective optimization. Operational Research Society, 57(10), 1143-1160.
36. Tayal, A. & Singh, S.P. (2017). Integrated SA-DEA-TOPSIS-based solution approach for multi-objective stochastic dynamic facility layout problem, International Journal of Business and Systems Research, 11(1/2), 82–100.
37. Tayal, A., & Singh, S. (2014). Chaotic Simulated Annealing for Solving Stochastic Dynamic Facility Layout Problem. Journal of International Management Studies, 14(2), 67-74.
38. Tavakkoli-Moghaddam, R., Javadian, N., Javadi, B., & Safaei, N. (2007). Design of a facility layout problem in cellular manufacturing systems with stochastic demands. Applied Mathematics and Computation, 184(2), 721-728.
39. Tompkins, J., White, J., Bozer, Y., Frazelle, E., Tanchoco, J., & Trevino, J. (2010). Facility planning 4th Edition. NY: John Wiley & Sons, New York, Inc.
40. Vitayasak, S., Pongcharoen, P., & Chris Hicks, C. (2016). A tool for solving stochastic dynamic facility layout problems with stochastic demand using either a Genetic Algorithm or modified Backtracking Search Algorithm. International Journal of Production Economics, 190, 146-157.