Presenting a Joint Replenishment-location Model Under all-units Quantity Discount and Solving by Genetic Algorithm and Harmony Search Algorithm
Subject Areas : Business and MarketingReza Abdollahi Sharbabaki 1 , Seyed Hamidreza Pasandideh 2
1 - Faculty of Industrial and Mechanical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran
2 - Faculty of Engineering, Department of Industrial Engineering, Kharazmi University, Tehran, Iran
Keywords:
Abstract :
Arkin, E., Joneja, D., Roundy, R. (1989). Computational complexity of uncapacitated multi-echelon production planning problems. Operations Research Letters. 8: 61-66.
Cha, BC., Moon, IK. (2005). The joint replenishment problem with quantity discounts under constant demand. Operational Research Spectrum. 27: 569-581.
Chan, C.K., Li, L.K., Ng, C.T., Cheung, B.K. (2006). Scheduling of multi-buyer joint replenishments. International Journal of Production Economics. 102: 132-142.
Chan, C.K., Cheung, B.K., Langevin, A. (2003). Solving the multi-buyer joint replenishment problem with a modified genetic algorithm. Transportation Research Part B: Methodological. 37 (3): 291-299.
Fung, R., Ma, X., (2001). A new method for joint replenishment problems. Journal of the Operational Research Society. 52: 358–362.
Geem, Z.W., Kim, J.H., Loganathan, G.V. (2001). A new heuristic optimization algorithm: harmony search. Simulations. 76: 60–68.
Goyal, S.K., Deshmukh, S.G. (1993). The economic ordering quantity for jointly replenishment items. International Journal of Production Research. 31: 109 -116.
Hariga, M. (1994). Two new heuristic procedures for the joint replenishment problem. Journal of the Operational Research Society. 45: 463-471.
Hoque, M.A. (2006). An optimal solution technique for the joint replenishment problem with storage and transport capacities and budget constraint. European Journal of Operational Research. 175:1033-1042.
Hong, S.P., Kim, Y.H. (2009). A genetic algorithm for joint replenishment based on the exact inventory cost. Computers & Operations Research. 6 (1): 167-175.
Hajipour, V., Rahmati, S.H. A., Pasandideh, S. H. R., Niaki, S.T.A. (2014). A Multi-Objective Harmony Search Algorithm to Optimize Multi-Server Location-Allocation Problem in Congested Systems. Computers & Industrial Engineering. 72:187-197.
Kaspi, M., Rosenblatt, M.J. (1991(. On the economic ordering quantity for jointly replenishment items. International Journal of Production Research. 29: 107–114.
Khouja, M., Goyal, S. (2008). A review of the joint replenishment problem literature: 1989–2005. European Journal of Operational Research. 186: 1–16.
Khouja, M., Michalewicz, Z., Satoskar, S. (2000). A comparison between genetic algorithms and the RAND method for solving the joint replenishment problem. Production Planning & Control: The Management of Operations. 11(6): 556-564.
Li Q. (2004). Solving the multi-buyer joint replenishment problem with the RAND method. Computers & Industrial Engineering. 46: 755-762.
Lu, T., Jia, S., Li, Y. (2010). A Modified RAND Algorithm for Multi-Buyer Joint Replenishment Problem with Resource Constraints. Information Science and Engineering, Hangzhou. China.
Lee, F.C., Yao, M.J. (2003). A global optimum search algorithm for the joint replenishment problem under power-of-two policy. Computers and Operations Research. 30: 1319-1333.
Olsen, A.L. (2005). An evolutionary algorithm to solve the joint replenishment problem using direct grouping. Computers & Industrial Engineering. 48: 223–235.
Porras, E., Dekker, R. (2006). An efficient optimal solution method for the joint replenishment problem with minimum order quantities. European Journal of Operational Research. 174: 1595-1615.
Qu, H., Wang, L., Zeng, Y.R. (2013). Modeling and optimization for the joint replenishment and delivery problem with heterogeneous items. Knowledge-Based Systems. 1-9.
[21] Qu, H., Wang, L., Liu, R. (2014). A Contrastive Study of the Stochastic Location-Inventory Problem with Joint Replenishment and Independent Replenishment. Expert Systems with Applications.
Silva, F., Gao, L. (2013). A Joint Replenishment Inventory-Location Model. Networks and Spatial Economics. 13: 107-122.
Taleizadeh, A.A., Niaki, S.T.A., Aryanezhad, M.B., Tafti, A.F. (2010). A genetic algorithm to optimize multiproduct multiconstraint inventory control systems with stochastic replenishment intervals and discount. Journal of advanced manufacturing Technology. 51: 311-323.
van Eijs, M.J.G. (1993). A note on the joint replenishment problem under constant demand. Journal of Operational Research Society. 44: 185-191.
Viswanathan, S. (1996). A new optimal algorithm for the joint replenishment problem. Journal of the Operational Research Society. 47: 936-944.
Wang, L., Dun, C.X., Bi, W.J., Zeng, Y.R. (2012). An effective and efficient differential evolution algorithm for the integrated stochastic joint replenishment and delivery model. Knowledge-Based Systems. 36: 104-114.
Wang, L., Qu, H., Liu, S., Chen, C. (2014). Optimizing the joint replenishment and channel coordination problem under supply chain environment using a simple and effective differential evolution algorithm. Discrete Dynamics in Nature and Society. Article ID 709856, 1–12, doi: /10.1155/2014/709856.