Determining Optimum Production Quantity on Multi-Product Home Textile Industry by Simulated Annealing
DOI:
https://doi.org/10.25126/jitecs.20183264Abstract
Production planning is a plan aimed at controlling the quantity of products produced. Production planning is very important to be carried out by the company so that the production will always be controlled. It is very difficult to plan production with a variety of product variations because each product certainly has a different demand value from its customers. This has become a complex problem so an algorithm is needed to overcome these problems. Simulated Annealing can produce optimal solutions more effectively and efficiently. Production costs generated by applying Simulated Annealing are Rp. 6,902,406,000, - for all types of products, which is better than existing condition.
References
R. Ramezanian, D. Rahmani, and F. Barzinpour, “An Aggregate Production Planning Model for Two Phase Production Systems: Solving with Genetic Algorithm and Tabu Search,†Expert Syst. Appl., vol. 39, pp. 1256–1263, 2012.
W. F. Mahmudy, “Optimization of Part Type Selection and Machine Loading Problems in Flexible Manufacturing System Using Variable Neighborhood Search,†IAENG Int. J. Comput. Sci., no. July, 2015.
W. H. M. Raaymakers and J. A. Hoogeveen, “Scheduling Multipurpose Match Process Industries with No-Wait Restrictions by Simulated Annealing,†Eur. J. Oper. Res., vol. 126, no. 1, pp. 131–151, 2000.
W. F. Mahmudy, “Improved Simulated Annealing for Optimization of Vehicle Routing Problem With Time Windows (VRPTW),†Kursor, vol. 7, no. 3, pp. 109–116, 2014.
T. Loukil, J. Teghem, and P. Fortemps, “A Multi-Objective Production Scheduling Case Study Solved by Simulated Annealing,†Eur. J. Oper. Res., vol. 179, no. 3, pp. 709–722, 2007.
T. B. Chistyakova, A. S. Razygrayev, and R. V Makaruk, “Decision Support System for Optimal Production Planning Polymeric Materials Using Genetic Algorithms,†in Soft Computing and Measurements (SCM), 2016, pp. 257–259.
H. J. Weiss and M. E. Gershon, Production and Operations Management, Second Edi. Massachusetts: Allyn & Bacon, 1993.
J. Heizer and B. Render, Production and Operations Management Strategies and Tactics. New Jersey: Prentice Hall, 1993.
S. Kirkpatrick, C. D. Gelatt, and M. P. Vecchi, “Optimization by Simulated Annealing,†Science (80-. )., vol. 220, no. 4598, pp. 671–680, 1983.
V. F. Yu, A. A. N. P. Redi, Y. A. Hidayat, and O. J. Wibowo, “A simulated annealing heuristic for the hybrid vehicle routing problem,†Appl. Soft Comput. J., vol. 53, pp. 119–132, 2017.
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