Abstract
A style dress outlet usually purchases products from multiple suppliers with different cost, quality and selling price. It is assumed that some suppliers will sell their goods to the buyer outright, while some other suppliers will offer return policy for items unsold. In the latter case, the supplier buys back from the buyer the unsold items at the end of the selling season. The purpose of this study is to enable the buyer to develop a supplier selection and replenishment policy subject to limited budget. A minimal service level and uncertain market are assumed as well. Genetic algorithm (GA) is used to solve the problem.
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References
Emmons, H., Gilbert, S.M.: The role of returns policies in pricing and inventory decisions for catalogue goods. Management Science 44(2), 277–283 (1998)
Mantrala, M.K., Raman, K.: Demand uncertainty and supplier’s returns policies for a multi-store style-good retailer. European Journal of Operational Research 115, 270–284 (1999)
Pasternack, B.A.: Optimal pricing and return policies for perishable commodities. Marketing Science 4(2), 166–176 (1985)
Padmanabhan, v., Png, I.P.L.: Returns policies: make money by making good. Sloan Management Review 37(1), 65–72 (1995)
Khouja, M.: The single-period (news-buyer) problem: literature review and suggestions for future research. The International Journal of Management Science 27, 537–553 (1999)
Hadley, G., Whitin, T.M.: Analysis of inventory systems. Prentice-Hall, Englewood Cliffs, NJ (1963)
Jucker, J.V., Rosenblatt, M.J.: Single-period inventory models with demand uncertainty and quantity discounts: behavioral implications and a new solution procedure. Naval Research Logistics 32, 537–550 (1985)
Gerchak, Y., Parlar, M.: A single period inventory problem with partially controlled demand. Computers and Operations Research 14(1), 1–9 (1987)
Lau, A.H.-L., Lau, H.-S.: The newsboy problem with price dependent distributions. IIE Transactions 20(2), 168–175 (1988)
Khouja, M.: The newsboy problem under progressive multiple discounts. European Journal of Operational Research 84, 458–466 (1995)
Khouja, M., Mehrez, A.: A multi-product constrained newsboy problem with progressive multiple discounts. Computers & Industrial Engineering 30, 95–101 (1996)
Lau, H.-S., Lau, A.H.-L.: The newsstand problem: A capacitated multi-product single-period inventory problem. European Journal of Operational Research 94, 29–42 (1996)
Pasternack, B.A.: The capacitated newsboy problem with revenue sharing. Journal of Applied Mathematics and Decision Sciences 5(10), 21–33 (2001)
Holland, J.H.: Adaptation in Natural and Artificial Systems. University of Michigan Press, Ann Arbor (1975)
Khouja, M., Michalewicz, Z., Wilmot, M.: The use of genetic algorithms to solve the economic lot size scheduling problem. European Journal of Operation Research 110, 509–524 (1998)
Jinxing, X., Jiefang, D.: Heuristic genetic algorithm for general capacitated lot-sizing problems. Computers and Mathematics with Applications 44, 263–276 (2002)
Mori, M., Tsent, C.C.: A genetic algorithm for multi-mode resource constrained project schedule problem. European Journal of Operation Research 100, 134–141 (1997)
Li, Y., Man, K.F., Tang, K.S.: Genetic algorithm to production planning and scheduling problems for manufacturing systems. Production Planning & Control 11(5), 443–458 (2000)
Poulos, P.N., Rigartos, G.G., Tzafestas, S.G., Koukos, A.K.: A Pareto-optimal genetic algorithm for warehouse multi-objective optimization. Engineering Applications of Artificial Intelligence 14, 737–749 (2001)
Zhou, G., Min, H., Gen, M.: A genetic algorithm approach to the bi-criteria allocation of customers to warehouses. International Journal of Production Economics 86, 35–45 (2003)
Aytug, H., Khouja, M., Vergara, F.E.: Use of genetic algorithms to solve production and operations management problems: a review. International Journal of Production Research 41(17), 3955–4009 (2003)
Altiparmak, F., Gen, M., Lin, L., Paksoy, T.: A genetic algorithm approach for multi-objective optimization of supply chain networks. Computers & Industrial Engineering 51, 197–216 (2006)
Coello, C.A.C., Veldhuizen, D.A.V., Lamont, G.B.: Evolutionary algorithms for solving problems. Kluwer Academic Publishers, New York (2002)
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Yang, P.C., Wee, H.M., Zahara, E., Kang, S.H., Tseng, Y.F. (2007). Supplier Selection for a Newsboy Model with Budget and Service Level Constraints. In: Gervasi, O., Gavrilova, M.L. (eds) Computational Science and Its Applications – ICCSA 2007. ICCSA 2007. Lecture Notes in Computer Science, vol 4705. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74472-6_46
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DOI: https://doi.org/10.1007/978-3-540-74472-6_46
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74468-9
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