Measuring the variability in supply chains with the peakedness

This paper introduces a novel way to measure the variability of order flows in supply chains, the peakedness. The peakedness can be used to measure the variability assuming the order flow is a general point pro- cess. We show basic properties of the peakedness, and demonstrate its computation from real-time continuous demand processes, and cumulative demand collected at fixed time intervals as well. We also show that the peakedness can be used to characterize demand, forecast, and inventory variables, to effectively manage the variability. Our results hold for both single stage and multistage inventory systems, and can further be extended to a tree-structured supply chain with a single supplier and multiple retailers. Furthermore, the peakedness can be applied to study traditional inventory problems such as quantifying bullwhip effects and determining safety stock levels. Finally, a numerical study based on real life Belgian supermarket data verifies the effectiveness of the peakedness for measuring the order flow variability, as well as estimating the bullwhip effects.variability, peakedness, supply chain

On regenerative processes and inventory control

In this paper we discuss a general framework for single item inventory control models. This framework is based on the regenerative structure of these models. Using results from the theory of regenerative processes a unified presentation of those models is presented. Although most of the results are already known for special cost structures this unified presentation yields us the possibility to show that the same techniques can be applied to each instance

Optimality of (s, S) Inventory Policies under Renewal Demand and General Cost Structures

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/142450/1/poms12795_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/142450/2/poms12795.pd

Unit demands inventory system with acceptance sampling

Ankara : The Department of Industrial Engineering and the Institute of Engineering and Sciences of Bilkent Univ. , 1989.Thesis (Master's) -- Bilkent University, 1989.Includes bibliographical references leaves 38.In this study, an extension to the unit demands inventory model with exponentially distributed interdemand times is considered. In this extension orders may arrive in two shipments due to an acceptance sampling scheme. The defective items that are detected by the plan will arrive through a second shipment. A reorder-point, order-quantity (s,Q) type control plan is adopted. The corresponding cost-rate function is constructed and numerically optimized for the best operating policy.Akbaş, ZekiM.S

Performance Evaluation of Stochastic Multi-Echelon Inventory Systems: A Survey

Globalization, product proliferation, and fast product innovation have significantly increased the complexities of supply chains in many industries. One of the most important advancements of supply chain management in recent years is the development of models and methodologies for controlling inventory in general supply networks under uncertainty and their widefspread applications to industry. These developments are based on three generic methods: the queueing-inventory method, the lead-time demand method and the flow-unit method. In this paper, we compare and contrast these methods by discussing their strengths and weaknesses, their differences and connections, and showing how to apply them systematically to characterize and evaluate various supply networks with different supply processes, inventory policies, and demand processes. Our objective is to forge links among research strands on different methods and various network topologies so as to develop unified methodologies.Masdar Institute of Science and TechnologyNational Science Foundation (U.S.) (NSF Contract CMMI-0758069)National Science Foundation (U.S.) (Career Award CMMI-0747779)Bayer Business ServicesSAP A