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Multiple-buyer multiple-vendor multi-product multi-constraint supply chain problem with stochastic demand and variable lead-time: A harmony search algorithm

Taleizadeh, A. A ; Sharif University of Technology | 2011

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  1. Type of Document: Article
  2. DOI: 10.1016/j.amc.2011.04.001
  3. Publisher: 2011
  4. Abstract:
  5. In this paper, a multi-buyer multi-vendor supply chain problem is considered in which there are several products, each buyer has limited capacity to purchase products, and each vendor has warehouse limitation to store products. In this chain, the demand of each product is stochastic and follows a uniform distribution. The lead-time of receiving products from a vendor to a buyer is assumed to vary linearly with respect to the order quantity of the buyer and the production rate of the vendor. For each product, a fraction of the shortage is backordered and the rest are lost. The ordered product quantities are placed in multiple of pre-defined packets and there are service rate constraints for the buyers. The goal is to determine the reorder points, the safety stocks, and the numbers of shipments and packets in each shipment of the products such that the total cost of the supply chain is minimized. We show that the model of this problem is of an integer nonlinear programming type and in order to solve it a harmony search algorithm is employed. To validate the solution and to compare the performance of the proposed algorithm, a genetic algorithm is utilized as well. A numerical illustration and sensitivity analysis are given at the end to show the applicability of the proposed methodology in real-world supply chain problems
  6. Keywords:
  7. Multi-vendor ; Harmony search algorithm ; Integer-nonlinear programming ; Multi-buyer ; Multi-vendor ; Partial back ordering ; Variable lead-time ; Genetic algorithms ; Integer programming ; Learning algorithms ; Nonlinear programming ; Optimization ; Sensitivity analysis ; Stochastic systems ; Supply chain management ; Sales
  8. Source: Applied Mathematics and Computation ; Volume 217, Issue 22 , July , 2011 , Pages 9234-9253 ; 00963003 (ISSN)
  9. URL: http://www.sciencedirect.com/science/article/pii/S009630031100542X