Simulated annealing and joint manufacturing batch-sizing
DOI:
https://doi.org/10.2298/YJOR0302245SKeywords:
inventory, procurement, periodic delivery, optimum order quantity, heuristic, simulated annealingAbstract
We address an important problem of a manufacturing system. The system procures raw materials from outside suppliers in a lot and processes them to produce finished goods. It proposes an ordering policy for raw materials to meet the requirements of a production facility. In return, this facility has to deliver finished products demanded by external buyers at fixed time intervals. First, a general cost model is developed considering both raw materials and finished products. Then this model is used to develop a simulated annealing approach to determining an optimal ordering policy for procurement of raw materials and also for the manufacturing batch size to minimize the total cost for meeting customer demands in time. The solutions obtained were compared with those of traditional approaches. Numerical examples are presented. .References
Sarker, R.A., Karim, A.N.M., and Azad, S., "Integrated inventory system: cases of product raw materials and producer-wholesalers", 37th Annual Convention of the Institution of Engineers Bangladesh, Rajshahi, Bangladesh, 1993.
Sarker, R.A., Karim, A.N.M., and Azad, S., "Two cases of integrated inventory", Journal of the Institution of Engineers, Bangladesh, 21 (4) (1995) 45-52.
Sarker, R.A., Karim, A.N.M., and Haque, A.F.M.A., "An optimal batch size for a production system operating under a continuous supply/demand", International Journal of Industrial Engineering, 2 (3) (1995) 189-198.
Sarker, B.R., and Parija, G.R., "An optimal batch size for a production system operating under a fixed-quantity, periodic delivery policy", Journal of the Operational Research Society, 45 (8) (1994) 891-900.
Jamal, A.M.M., and Sarker, B.R., "An optimal batch size for a production system operating under a just-in-time delivery system", International Journal of Production Economics, 32 (2) (1993) 255-260.
Golhar, D.Y., and Sarker, B.R., "Economic manufacturing quantity in a just-in-time delivery system", International Journal of Production Research, 30 (5) (1992) 961-972.
Sarker, B.R., and Golhar, D.Y., "A reply to 'A note to "Economic manufacturing quantity in a just-in-time delivery system"', International Journal of Production Research, 31 (11) (1993) 27-49.
Sarker, B.R., and Parija, G.R., "Optimal batch size and raw material ordering policy for a production system with a fixed-interval, lumpy demand delivery system", European Journal of Operational Research, 89 (1996) 593-608.
Metropolis, N., Rosenbluth, A., Rosenbluth, M., and Teller, E., "Equations of state calculations by fast computing machines", Journal of Chemical Physics, 21 (1953) 1087-1091.
Kirkpatrick, S., Gelatt, C.D., and Vecchi, M.P., "Optimization by simulated annealing", Science, 220 (1983) 671-680.
Yao, X., "A new simulated annealing algorithm", International Journal of Computer Mathematics, 56 (1995) 161-168.
Yao, X., "Call routing by simulated annealing", International Journal of Electronics, 79 (4) (1995) 379-387.
Moinzadeh, K., and Aggarwal, P., "Order expedition in multi-level production inventory system", Paper presented at TIMS/ORSA Joint National Meeting, Las Vegas, NV, USA, May 7-9, 1990.
Silver, E.A., Pyke, D.F., and Peterson, R., Inventory Management and Production Planning and Scheduling, (3rd ed.), John Wiley & Sons, New York, 1998.
Joglekar, P., and Tharthare, S., "The individually responsible and rational decision approach to economic lot sizes for one vendor and many purchasers", Decision Sciences, 21 (1990) 492-506.
Yao, X., "Simulated annealing with extended neighbourhood size", International Journal of Computer Mathematics, 41 (1991).
Goyal, S.K., "An integrated inventory model for a single product system", Operational Research Quarterly, 28 (1977) 539-545.
Adil, G.K., Rajamni, D., and Strong, D., "Assignment allocation and simulated annealing algorithms for cell formulation", IIE Transactions, (1997) 53-67.
Gemmill, D.D., and Tsai, Y.-W., "Using a simulated annealing algorithm to schedule activities of resource-constrained projects", Project Management Journal, (1997) 8-20.
Khan, Z., Prasad, B., and Singh, T., "Machining condition optimization by genetic algorithms and simulated annealing", Computers & Operations Research, (1967) 647-657.
Kim, J.-U., and Kim, Y.-D., "Simulated annealing and genetic algorithms for scheduling products with multi-level product structure", Computers & Operations Research, (1996) 857-868.
Koulaman, C., Antony, S.R., and Jean, R., "A survey of simulated annealing applications to operations research problems", Omega, 22 (1994) 41-56.
Kuik, R., and Salomon, M., "Multi-level lot sizing problems: evaluation of a simulated annealing heuristics", European Journal of Operational Research, 45 (1990) 25-37.
Kuik, R., Salomon, M., Wassenhove, L.N., and Maes, J., "Linear programming, simulated annealing and tabu search heuristics for lotsizing in bottleneck assembly systems", IIE Transactions, 25 (1993) 62-72.
Parada, V., Sepulveda, M., and Solar, M., "Solution for the constrained guillotine cutting problem by simulated annealing", Computers & Operations Research, (1998) 37-47.
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