Ashis Kumar Chatterjee

Leveraging information in multi-echelon inventory systems

Abstract Decision-making in multi-echelon inventory systems is often facilitated by the availability of information. In this paper, we examine the effect of utilising demand information in a one-warehouse two-retailer system operating under periodic-review. A common and fixed replenishment interval is assumed for all stages. The lead times are deterministic, and are small compared to the replenishment interval. The warehouse does not maintain any cycle stock, i.e., as soon as replenishment arrives at the warehouse, retailers’ demands are fulfilled from the available stock. In the event of a shortage at the warehouse, two cases have been considered––emergency shipment and allocation. For both the cases, expected total cost (ETC) models have been developed, and it has been shown through numerical examples that the optimal ETC in the presence of demand information is always lower than that in the absence of demand information. It is also noted that the order-up-to level at the warehouse has to be dynamic to reap the benefits of availability of demand information.

Vendor managed inventory for single-vendor multi-retailer supply chains

Vendor managed inventory (VMI) as a supply chain coordination mechanism has been gaining a lot of attention. This paper develops analytical models for various approaches through which a single vendor-multiple retailer system may be coordinated through VMI. Through detailed analysis of the parameters involved, we discuss the conditions under which each of these approaches may be preferred. We also highlight the savings that can be derived in the transportation cost in a VMI setting. Different ways of structuring the replenishment policy under VMI have been considered.Models have been developed to exploit different cost trade-offs in the supply chain.Significant cost reduction is possible across different policies.Implications of adopting different models have been analyzed.

VMI for single-vendor multi-retailer supply chains under stochastic demand ☆

Abstract This paper discusses how a vendor and multiple retailers interact in a vendor managed inventory (VMI) system under stochastic demand. It is assumed that the vendor replenishes all the retailers at the same time. The vendor replenishment cycle is taken to be an integer multiple of the retailer replenishment cycle. In case of a shortage at the vendor, the available stock is allocated to the retailers on the basis of equal stock out probability. Approximate expressions for minimizing the expected total cost for the VMI system have been developed. Various levers affecting the performance of the system have been analyzed. The validity of the approximate model has been tested through simulation.

A vendor-managed inventory scheme as a supply chain coordination mechanism

In this paper, we have considered a vendor-managed inventory (VMI) arrangement in a supply chain (SC), where the buyer imposes a penalty for shipments exceeding an upper limit. We have shown as how the industry practice of VMI under penalty can be used as a SC coordination mechanism. The vendor can influence the buyer to increase the batch size without making the buyer worse off. We also discuss how such a penalty scheme may be derived. Further, we have established the equivalence of VMI under deterministic demand with that of quantity discount models, thus highlighting the need to incorporate both cooperation and coordination perspectives while analysing SC collaboration mechanisms.

Joint replenishment of multi retailer with variable replenishment cycle under VMI

In the recent article, Darwish and Odah (2010) develop a scheme that allows for identical replenishment cycles for all the retailers, in the context of a single vendor supplying a group of retailers under VMI partnership. This paper proposes an alternative replenishment scheme allowing for different replenishment cycles for each retailer. An example has been shown to illustrate the cost savings under the proposed model.

A heuristic-based approach to integrate the product line selection decision to the supply chain configuration

Product platform development (PPD) as an approach to mass customisation (MC) helps an organisation to reduce costs as well as ensure timely deliveries. Varieties are offered to different market segments by combining and incorporating different modules at different levels. Modules at different levels are essentially features that a customer segment is looking for. It is apparent that overall optimisation would require simultaneous consideration of not only PPD but also other supply chain constraints. In this paper, an attempt has been made to develop a mixed integer linear programming (MILP) model for sourcing, production planning, and PPD decisions. Based on analyses of the model, a heuristic solution procedure has been suggested. The heuristic developed in this paper attempts to decompose the problem and then assimilate the outputs from the simpler parts to obtain the final solution. Finally, a simple example to illustrate the solution procedure is presented.

Impact of structure, market share and information asymmetry on supply contracts for a single supplier multiple buyer network

Market share of buyers and the influence of supply chain structure on the choice of supply contracts have received scant attention in the literature. This paper focuses on this gap and examines a network consisting of one supplier and two buyers under complete and partial decentralization. In the completely decentralized setting both buyers are independent of the supplier. In the partially decentralized setting the supplier and one of the buyers form a vertically integrated entity. Both buyers order from the single supplier and produce similar products to sell in the same market. The supplier charges the buyer through a contract. We investigate the influence of supply chain structure, market-share and asymmetry of information on suppliers choice of contracts. We demonstrate that both linear two-part tariff and quantity discount contract can coordinate the supply chain irrespective of the supply chain structure. By comparing profit levels of supply chain agents across different supply chain structures, we show that if a buyer possesses a minimum threshold market potential, the supplier has an incentive to collude with her. We calculate the cut-off policies for wholesale price and two-part tariff contracts by incorporating the reservation profit level of individual agents. The managerial implications of the analyses and the directions of future research are presented in the conclusion.

Applying machine based decomposition in 2-machine flow shops

The Shifting Bottleneck (SB) heuristic is among the most successful approximation methods for solving the Job Shop problem. It is essentially a machine based decomposition procedure where a series of One Machine Sequencing Problems (OMSPs) are solved. However, such a procedure has been reported to be highly ineffective for the Flow Shop problems (Jain and Meeran 2002). In particular, we show that for the 2-machine Flow Shop problem, the SB heurisitc will deliver the optimal solution in only a small number of instances. We examine the reason behind the failure of the machine based decomposition method for the Flow Shop. An optimal machine based decomposition procedure is formulated for the 2-machine Flow Shop, the time complexity of which is worse than that of the celebrated Johnsons Rule. The contribution of the present study lies in showing that the same machine based decomposition procedures which are so successful in solving complex Job Shops can also be suitably modified to optimally solve the simpler Flow Shops.

The average shadow price for MILPs with integral resource availability and its relationship to the marginal unit shadow price

Abstract The economic significance of the average shadow price for integer and mixed integer linear programming (MILP) problems has been established by researchers [Kim and Cho, Eur. J. Operat. Res. 37 (1988) 328; Crema Eur. J. Operat. Res. 85 (1995) 625]. In this paper we introduce a valid shadow price ( ASPIRA ) for integer programs where the right-hand side resource availability can only be varied in discrete steps. We also introduce the concept of marginal unit shadow price ( MUSP ). We show that for integer programs, a sufficient condition for the marginal unit shadow price to equal the average shadow price is that the Law of Diminishing Returns should hold. The polyhedral structures that will guarantee this equivalence have been explored. Identification of the problem classes for which the equivalence holds complements the existing procedure for determining shadow price for such integer programs. The concepts of ASPIRA and MUSP introduced in this paper can play a vital role in resource acquisition plans and in defining efficient market clearing prices in the presence of indivisibilities.

On the representation of the one machine sequencing problem in the shifting bottleneck heuristic

The Shilling Bottleneck heuristic decomposes the Job Shop problem into a series of One Machine Sequencing Problems (OMSPs) with release and due dates, precedence constraints and the minimization of maximum lateness objective. It is well known that delayed precedence constraints may exist between two operations to be performed on the same machine. We identify a new type of precedence constraint that may exist in an OMSP between the predecessor of an operation and the successor of another. The premise that an OMSP captures the sequencing relationships on other machines in the release and due date information is not valid when such precedence constraints exist. A modification of the OMSP representation is proposed based on a generalized lateness objective defined on a due window. The implications of such a representation for the OMSP solution procedure have been explored.