Showing papers by "Chandrasekharan Rajendran published in 2014"

The value of information sharing in a multi-product, multi-level supply chain: Impact of product substitution, demand correlation, and partial information sharing

Abstract: The literature on the value of information sharing within a supply chain is extensive. The bulk of the literature has focused on two-level supply chains that supply a single product. However, modern supply chains often have more than two levels and supply many products. Because many of these products are variants of the same base product, they tend to be substitutes and their demands correlated. Further, achieving supply-chain-wide information sharing in a multi-level supply chain is challenging because different firms may have different levels of incentives to share information. We analyze the value of information sharing using a comprehensive supply chain that has multiple levels, may have different degrees of information sharing, and supplies multiple products that may have different levels of substitutability and whose demands could be correlated to different degrees. Our analysis shows that substitution among the different products reduces the value of information sharing for all firms in the supply chain. The reduction is higher (i) for firms that are more upstream, (ii) when the degree of substitution is higher, (iii) when the number of substitutable products is higher, (iv) when the demands of products are more correlated, and (v) when the degree of information sharing is higher. Our results suggest that firms, especially those that are upstream in the supply chain, may face a significant risk of over-estimating the value of information sharing if they ignore substitution, demand correlation, and partial information sharing effects.

Distribution and Equitable Sharing of Value From Information Sharing Within Serial Supply Chains

Abstract: This paper studies the incentive issues that arise when firms in a multilevel supply chain create value jointly by investing in information sharing. We consider three types of information sharing: (1) supply-chain-wide information sharing; (2) downstream information sharing; and (3) upstream information sharing. We showed that the value of information sharing is higher for the upstream firms than for downstream firms regardless of information sharing type. Furthermore, the value of information sharing for any firm is higher under downstream information sharing than upstream information sharing, and the incremental value of information sharing to a firm decreases when more downstream firms share information. Therefore, if there is a cost associated with information sharing, then upstream firms have an incentive to free ride on downstream firms' information sharing efforts. These results suggest that serious incentive misalignments may impede supply-chain-wide information sharing, even though it maximizes the value to the supply chain, and that a mechanism to distribute the overall surplus equitably may become essential. If a contract distributes the surplus according to each firm's incremental contribution to it, then firms that are in the middle levels of the supply chain receive a higher share than those that are in either end of the supply chain. That is, interestingly, neither the firm that possesses the information that is propagated throughout the supply chain by information sharing nor the most upstream firm realizes the highest value from information sharing obtains the maximum share of the surplus generated under such a contract.

A Comparative Study of Periodic-Review Order-Up-To (T, S) Policy and Continuous-Review (s, S) Policy in a Serial Supply Chain Over a Finite Planning Horizon

Abstract: In this paper, we consider a serial supply chain (SC) operating with deterministic and known customer demands and costs of review or orders, holding, and backlog at every installation over a finite planning horizon. We present an evaluation of two order policies: Periodic-review order-up-to S policy (i.e., (T, S) policy), and (s, S) policy. We first present a mathematical programming model to determine optimal re-order point and base-stock for every member in the SC. By virtue of the computational complexity associated with the mathematical model, we present genetic algorithms (GAs) to determine the order policy parameters, s and S for every stage. We compare the performances of GAs (for obtaining installation s and S) with the mathematical model for the periodic-review order-up-to (T, S) policy that obtains in its class optimal review periods and order-up-to levels. It is observed that the (s, S) policy emerges to be mostly better than the (T, S) policy.

The Value of Information Sharing in a Multi-Stage Serial Supply Chain with Positive and Deterministic Lead Times

Abstract: In traditional supply chain inventory management, orders used to be the major information that firms exchanged. Information sharing among firms within a supply chain has been a cornerstone of recent innovations in supply chain management. Lee et al. (2000) considered a two-level supply chain, consisting of a manufacturer and a retailer, with non-stationary AR(1) end demand and showed that the manufacturer benefits significantly when the retailer shares its demand information. In our work, we extend the study to quantify the value (i.e., benefit) of information sharing (in terms of demand variance reduction and inventory reduction) to a multi-stage serial supply chain with the number of stages greater than two. The lead time at every stage is positive and deterministic. Base stock levels at each installation are calculated under two scenarios—no information sharing and complete information sharing. The dependency of the benefit of information sharing on parameters like demand correlation and lead times is presented. It is seen that as the number of stages in a serial supply chain increases, the demand variance and hence the bullwhip effect increases; so is the case with an increase in the demand correlation. In addition, a comparative study of a supply chain with stages having respective lead times in decreasing order and a supply chain with stages having respective lead times in increasing order has also been carried out in order to relatively analyze the benefits of information sharing at different stages across these two supply chain settings. It is possibly for the first time in the literature that the benefit of information sharing has been studied and quantified (in terms of the reduction in the total demand variation and the reduction in inventory) in a multi-stage serial supply chain with more than three stages with positive and deterministic lead times.

A heuristic algorithm to minimise the total flowtime of jobs in permutation flowshops

Abstract: A heuristic algorithm with six implementations (HA-I to HA-VI) is presented in this paper, and it is used to solve the permutation flowshop scheduling problem to minimise the total flowtime of jobs. These implementations have been evaluated by using the 90 benchmark flowshop scheduling problem instances, and the solutions yielded are compared with the solutions reported in the literature. The comparison shows that the implementations all together have produced better solutions for 28 problem instances and same solutions for 29 problem instances, out of 90 problem instances considered with respect to the solutions by Iterated Local Search algorithm proposed by Dong et al. (2009). They have also produced better solutions for 50 problem instances and the same solutions for 19 problem instances, out of 90 problem instances considered with respect to the solutions by PSOvns algorithm proposed by Tasgetiren et al. (2007), as reported in Dong et al. (2009).