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http://sim.sagepub.com A Simulation Model for Multi-Product Inventory Control Management Masood A. Badri SIMULATION 1999; 72; 20 DOI: 10.1177/003754979907200103 The online version of this article can be found at: http://sim.sagepub.com/cgi/content/abstract/72/1/20

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A Simulation Model for Multi-Product

Inventory Control Management
Masood A. Badri
United Arab Emirates University Faculty of Business & Economics Department of Business Administration Al-Ain, United Arab Emirates E-mail: Masood@uaeu.ac.ae

A simulation based-decision support system for multi-product inventory control management is developed. The system permits management to obtain an inventory system-wide view of the effect of changes in decision variables on the performance measures of a furniture manufacturing firm. The simulation model considers the effect of variations in demand, re-order point, stock-control level, time between reviews, and lead time. The decision support system generates policy scenarios based on management specifications. The effect of each scenario on system performance is then analysed. A set of search methods is combined with the DSS to aid in the optimisation process. The developed network consists of three basic sub-networks. The first sub-network represents the demand, backorder, and stock components of the system. The second network represents the periodic review

1. Introduction Since well managed inventories help reduce both direct expenses of a business plus its investment base (and keep customers happier, too), the business return on investment can be dramatically improved. Efficient inventory control is a challenge for any organisation that must maintain substantial investments in inventory, such as a furniture manufacturing firm. Demands

imposed on an inventory by customers seeking supplies of the items. To compete in today’s highly competitive markets, a company must establish an inventory policy that specifies (1) when an order for additional items should be placed, and (2) how many are

process with stock control levels for each product. The third sub-network performs profit and cost calculations under normal circumstances and when lost sales are present.

items should be ordered at each order time [1, 2]. The answer to these two questions depends on the revenues and costs associated with the inventory situation. Inventory theory deals with the determination of the best inventory policy [2, 3]. Equations have been developed for setting parameter values in specific situations. These equations, however, are based on restrictive assumptions to make the analysis traceable. Through computer simulation, such assumptions can be avoided [4, 5, 6, 7]. Obviously, the simulation approach requires many more calculations than do ana-

Keywords: Inventory control, decision support system, SLAMSYSTEM, multi-product inventory, backorders, lost sales

lytic counterparts. Nevertheless, computations are simple to understand and do, especially with the availability of special purpose simulation package [8, 9,10]. Decision support systems (DSS) provide an opportunity to apply operations research tools to many

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