Continuous review inventory model with controllable lead time,lost sales rate and order processing cost when the received quantity is uncertain |
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| Affiliation: | 1. Department of Mechanical Engineering, Ecole de Technologie Superieure, 1100 Notre Dame West, Montreal, Quebec, Canada;2. Department of System Engineering, Ecole de Technologie Superieure, 1100 Notre Dame West, Montreal, Quebec, Canada;1. School of Industrial Engineering, College of Engineering, University of Tehran, Iran;2. School of Industrial Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran;3. Center for Sustainable Supply Chain Engineering, Department of Technology and Innovation, University of Southern Denmark, Odense M, 5230, Denmark;1. School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran;2. Palumbo-Donahue Schools of Business, Duquesne University, Pittsburgh, PA 15282, USA;1. Operations Research and Logistics, Wageningen University, Hollandseweg 1, 6706 KN Wageningen, The Netherlands;2. Logistics and Supply Chain Management, Technische Universität München, TUM School of Management, Arcisstr. 21, 80333 Munich, Germany |
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| Abstract: | In practice the quantity received may not match the quantity ordered due to worker's strike, rejection during inspection, damage during transportation, human errors in counting, etc. Accordingly, the managers often must make decisions under uncertain quantity received circumstances. In this study, we investigate the continuous review inventory model with shortages include the case where the quantity received is uncertain, in which the lead time, lost sales rate and order processing cost are decision variables. Here, we consider the lead time crashing cost is an exponential function of lead time, and the order processing cost and lost sales rate are logarithmic functions of capital investment. The objective of this study is to minimize the total relevant cost by simultaneously optimizing the order quantity, lost sales rate and order processing cost. In addition, an efficient algorithm is developed to determine the optimal policy, and our approach is illustrated through a numerical example. From the results of numerical example, it can be shown that, the significant savings can be achieved through the reductions of order processing cost and lost sales rate. |
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| Keywords: | Continuous review Shortage Crashing cost Order processing cost Investment |
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