Title: Consignment stock policy using genetic algorithm for effective inventory management in supply chains

Authors: Ch. Srinivas, C.S.P. Rao, Y.V. Rao

Addresses: Manufacturing Simulation Laboratory, Department of Mechanical Engineering, National Institute of Technology, Warangal, Andhra Pradesh, India. ' Manufacturing Simulation Laboratory, Department of Mechanical Engineering, National Institute of Technology, Warangal, Andhra Pradesh, India. ' Manufacturing Simulation Laboratory, Department of Mechanical Engineering, National Institute of Technology, Warangal, Andhra Pradesh, India

Abstract: In this paper, we consider single-vendor–multi-buyer Consignment Stock Policy (CSP) inventory model which is a distinctive flavour of Vendor Managed Inventory (VMI). Four different models have been formulated using Genetic Algorithm (GA) to minimise joint total expected cost of vendor and buyer and simultaneously optimise other decision variables such as quantity transported, number of transport operations, delay deliveries and buyer maximum and minimum stocks under stochastic environment. Numerical examples are presented to illustrate the proposed models, and the effects of changes on the cost and system parameters on the inventory are studied by using sensitivity analysis. To solve the iterative procedure involved, the GA is coded in VC++.

Keywords: consignment stock policy; CSP; supply chain management; SCM; genetic algorithms; GAs; delay delivery; information sharing; crashing cost; inventory management; vendor managed inventory; VMI.

DOI: 10.1504/IJSOI.2008.019328

International Journal of Services Operations and Informatics, 2008 Vol.3 No.2, pp.107- 126

Available online: 07 Jul 2008 *

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