1,721,132 research outputs found
Competition in the Supply Option Market
Full text linkThis paper develops a multiattribute competition model for procurement of short life-cycle products. In such an environment, the buyer installs dedicated production capacity at the suppliers before demand is realized. Final production orders are decided after demand materializes. Of course, the buyer is reluctant to bear all the capacity and inventory risk, and thus signs flexible contracts with several suppliers. We model the suppliers' offers as option contracts, where each supplier charges a reservation price per unit of capacity and an execution price per unit of delivered supply. These two parameters illustrate the trade-off between total price and flexibility of a contract, which are both important to the buyer. We model the interaction between suppliers and the buyer as a game in which the suppliers are the leaders and the buyer is the follower. Specifically, suppliers compete to provide supply capacity to the buyer, and the buyer optimizes its expected profit by selecting one or more suppliers. We characterize the suppliers' equilibria in pure strategies for a class of customer demand distributions. In particular, we show that this type of interaction gives rise to cluster competition. That is, in equilibrium suppliers tend to be clustered in small groups of two or three suppliers each, such that within the same group all suppliers use similar technologies and offer the same type of contract. Finally, we show that in equilibrium, supply chain inefficiencies—i.e., the loss of profit due to competition—are at most 25% of the profit of a centralized supply chain.United States. Office of Naval Research (contract N00014-95-1-0232)United States. Office of Naval Research (contract N00014-01-1-0146)National Science Foundation (U.S.) (contract DMI-0085683)National Science Foundation (U.S.) (DMI-0245352)National Science Foundation (U.S.) (CMMI-0758069)Massachusetts Institute of Technology. Center for Digital BusinessUniversity of Navarra. IESE Business School (CIIL International Center for Logistics Research
Optimal static pricing for a tree network
Full text linkWe study the static pricing problem for a network service provider in a loss system with a tree structure. In the network, multiple classes share a common inbound link and then have dedicated outbound links. The motivation is from a company that sells phone cards and needs to price calls to different destinations. We characterize the optimal static prices in order to maximize the steady-state revenue. We report new structural findings as well as alternative proofs for some known results. We compare the optimal static prices versus prices that are asymptotically optimal, and through a set of illustrative numerical examples we show that in certain cases the loss in revenue can be significant. Finally, we show that static prices obtained using the reduced load approximation of the blocking probabilities can be easily obtained and have near-optimal performance, which makes them more attractive for applications.Massachusetts Institute of Technology. Center for Digital BusinessUnited States. Office of Naval Research (Contract N00014-95-1-0232)United States. Office of Naval Research (Contract N00014-01-1-0146)National Science Foundation (U.S.) (Contract DMI-9732795)National Science Foundation (U.S.) (Contract DMI-0085683)National Science Foundation (U.S.) (Contract DMI-0245352
Multiship Crane Sequencing with Yard Congestion Constraints
Full text linkCrane sequencing in container terminals determines the order of ship discharging and loading jobs that quay cranes (QCs) perform, so that the duration of a vessel's stay is minimized. The ship's load profile, berthing time, number of available bays, and QCs are considered. More important, clearance and yard congestion constraints need to be included, which, respectively, ensure that a minimum distance between adjacent QCs is observed and yard storage blocks are not overly accessed at any point in time. In sequencing for a single ship, a mixed-integer programming (MIP) model is proposed, and a heuristic approach based on the model is developed that produces good solutions. The model is then reformulated as a generalized set covering problem and solved exactly by branch and price (B&P). For multiship sequencing, the yard congestion constraints are relaxed in the spirit of Lagrangian relaxation, so that the problem decomposes by vessel into smaller subproblems solved by B&P. An efficient primal heuristic is also designed. Computational experiments reveal that large-scale problems can be solved in a reasonable computational time
Optimal Expediting Policies for a Serial Inventory System with Stochastic Lead Time
No full textIn recent supply chains, often operating multiple delivery modes such as standard freight shipping and air is an effective way of addressing both delivery lead time uncertainties and service rates. We propose a model on how to optimally operate multiple delivery modes. We consider a serial supply chain and an expediting option from intermediate installations to the downstream of the chain. The goods move stochastically among the installations and the system faces a stochastic demand. We identify systems that yield simple optimal policies, in which both regular ordering and expediting follow a variant of the base stock policy. Expediting allows the system to be leaner due to the reduced regular order amount. In addition, we provide managerial insights linking expediting, base stock levels, and expediting costs based on analytical and numerical results
Supplier-Buyer Negotiation Games: Equilibrium Conditions and Supply Chain Efficiency
Full text linkIn a decentralized supply chain, supplier–buyer negotiations have a dynamic aspect that requires both players to consider the impact of their decisions on future decisions made by their counterpart. The interaction generally couples strongly the price decision of the supplier and the quantity decision of the buyer. We propose a basic model for a repeated supplier–buyer interaction, during several rounds. In each round, the supplier first quotes a price, and the buyer places an order at that price. We find conditions for existence and uniqueness of a well-behaved subgame-perfect equilibrium in the dynamic game. When costs are stationary and there are no holding costs, we identify some demand distributions for which these conditions are met, examine the efficiency of the equilibrium, and show that, as the number of rounds increases, the profits of the supply chain increase towards the supply chain optimum. In contrast, when costs vary over time or holding costs are present, the benefit from multi-period interactions is reduced and after a finite number of time periods, supply chain profits stay constant even when the number of rounds increases
Analyzing process flexibility: A distribution-free approach with partial expectations
Full text linkWe develop a distribution-free model to evaluate the performance of process flexibility structures when only the mean and partial expectation of the demand are known. We characterize the worst-case demand distribution under general concave objective functions, and apply it to derive tight lower bounds for the performance of chaining structures under the balanced systems (systems with the same number of plants and products). We also derive a simple lower bound for chaining-like structures under unbalanced systems with different plant capacities. Keywords:
Process flexibility; Distributionally-robust analysis; Chaining; Production system desig
Reengineering Management Science for a Sharper Focus and Broader Appeal
No full textManagement Science is a scholarly journal that publishes scientific research on the practice of management. Therefore, papers published in Management
Science should deal with issues and problems important to managers and executives; they must be interesting to a wide range of people in the management science community; and they should have the potential
to impact management practice
A carbon-capped supply chain network problem
No full textThe Kyoto protocol was negotiated as a global effort to reduce greenhouse gas (GHG) emissions. The future standing of companies will be seriously affected by the steps they take today in regards to the environment. Perhaps, if vigilant actions are not taken by a firm then it could easily be left behind in today's highly competitive world. This paper presents a novel optimization model for green supply chain management, which integrates environmental management and its impact into the supply chain while taking carbon emissions into account. The model, which we formulate as a mixed-integer program (MIP), can help to reveal an optimal strategy for companies to meet their carbon cap, while minimizing opportunity cost. We demonstrate the viability of the model via a computational study.Massachusetts Institute of TechnologyMasdar Institute of Science and Technolog
A carbon sensitive supply chain network problem with green procurement
No full textFaced with growing concerns over the environmental impact of human activities and increasing regulatory pressure, companies are beginning to recognize the importance of greening their supply chains by minimizing carbon emissions of their activities. An original equipment manufacturer that is concerned with minimizing the environmental impact of its activities should choose its suppliers based on the trade off between costs and respective emissions. In this paper, we develop an MIP model for the carbon-sensitive supply chain that minimizes emissions throughout the supply chain by taking into consideration green procurement. A sensitivity analysis of our model and results on several small problems are included.Massachusetts Institute of TechnologyMasdar Institute of Science and Technolog
Robust Stochastic Lot-Sizing by Means of Histograms
Full text linkTraditional approaches in inventory control first estimate the demand distribution among a predefined family of distributions based on data fitting of historical demand observations, and then optimize the inventory control using the estimated distributions. These approaches often lead to fragile solutions whenever the preselected family of distributions was inadequate. In this article, we propose a minimax robust model that integrates data fitting and inventory optimization for the single-item multi-period periodic review stochastic lot-sizing problem. In contrast with the standard assumption of given distributions, we assume that histograms are part of the input. The robust model generalizes the Bayesian model, and it can be interpreted as minimizing history-dependent risk measures. We prove that the optimal inventory control policies of the robust model share the same structure as the traditional stochastic dynamic programming counterpart. In particular, we analyze the robust model based on the chi-square goodness-of-fit test. If demand samples are obtained from a known distribution, the robust model converges to the stochastic model with true distribution under generous conditions. Its effectiveness is also validated by numerical experiments.National Science Foundation (U.S.) (Contract CMMI-0758069
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