Overview and classification of coordination contracts within forward and reverse supply chains

Among coordination mechanisms, contracts are valuable tools used in both theory and practice to coordinate various supply chains. The focus of this paper is to present an overview of contracts and a classification of coordination contracts and contracting literature in the form of classification schemes. The two criteria used for contract classification, as resulted from contracting literature, are transfer payment contractual incentives and inventory risk sharing. The overview classification of the existing literature has as criteria the level of detail used in designing the coordination models with applicability on the forward and reverse supply chains.Coordination contracts; forward supply chain; reverse supply chain

Development Of Model For Supplier Selection And Order Allocation With Discount Pricing And Expected Quality Loss

This paper discusses the development of optimization model for supplier selection and order allocation considering price discounts and quality of the components that are measured based on expectation of quality loss cost. The approach which was used quadratic loss function to estimated quality loss. The development of model is based on the drawback of previous research; where quality was measured only by defective components without considered to any loss of quality due to deviation from quality characteristics target. In the section of results and discussion of this paper is presented a numerical example in order to illustrate the implementation of proposed model. This numerical experiment performed by optimization software has indicated that the model able to generated optimal solution. Keywords- optimization model, supplier selection, price, discount, quality los

A single buyer-single supplier bargaining problem with asymmetric information : theoretical approach and software implementation

This paper is focused on the coordination of order and production policy between buyers and suppliers in supply chains. When a buyer and a supplier of an item work independently, the buyer will place orders based on his economic order quantity (EOQ). However, the buyer s EOQ may not lead to an optimal policy for the supplier. It can be shown that a cooperative batching policy can reduce total cost significantly. Should the buyer have the more powerful position to enforce his EOQ on the supplier, then no incentive exists for him to deviate from his EOQ in order to choose a cooperative batching policy. To provide an incentive to order in quantities suitable to the supplier, the supplier could offer a side payment. One critical assumption made throughout in the literature dealing with incentive schemes to influence buyer s ordering policy is that the supplier has complete information regarding buyer s cost structure. However, this assumption is far from realistic. As a consequence, the buyer has no incentive to report truthfully on his cost structure. Moreover there is an incentive to overstate the total relevant cost in order to obtain as high a side payment as possible. This paper provides a bargaining model with asymmetric information about the buyer s cost structure assuming that the buyer has the bargaining power to enforce his EOQ on the supplier in case of a break-down in negotiations. An algorithm for the determination of an optimal set of contracts which are specifically designed for different cost structures of the buyer, assumed by the supplier, will be presented. This algorithm was implemented in a software application, that supports the supplier in determining the optimal set of contracts

A Stochastic Dynamic Programming Approach to Revenue Management in a Make-to-Stock Production System

In this paper, we consider a make-to-stock production system with known exogenous replenishments and multiple customer classes. The objective is to maximize profit over the planning horizon by deciding whether to accept or reject a given order, in anticipation of more profitable future orders. What distinguishes this setup from classical airline revenue management problems is the explicit consideration of past and future replenishments and the integration of inventory holding and backlogging costs. If stock is on-hand, orders can be fulfilled immediately, backlogged or rejected. In shortage situations, orders can be either rejected or backlogged to be fulfilled from future arriving supply. The described decision problem occurs in many practical settings, notably in make-to-stock production systems, in which production planning is performed on a mid-term level, based on aggregated demand forecasts. In the short term, acceptance decisions about incoming orders are then made according to stock on-hand and scheduled production quantities. We model this problem as a stochastic dynamic program and characterize its optimal policy. It turns out that the optimal fulfillment policy has a relatively simple structure and is easy to implement. We evaluate this policy numerically and find that it systematically outperforms common current fulfillment policies, such as first-come-first-served and deterministic optimization.revenue management;advanced planning systems;make-to-stock production;order fulfillment

Applying Revenue Management to the Reverse Supply Chain

We study the disposition decision for product returns in a closed-loop supply chain. Motivated by the asset recovery process at IBM, we consider two disposition alternatives. Returns may be either refurbished for reselling or dismantled for spare parts. Reselling a refurbished unit typically yields higher unit margins. However, demand is uncertain. A common policy in many firms is to rank disposition alternatives by unit margins. We show that a revenue management approach to the disposition decision which explicitly incorporates demand uncertainty can increase profits significantly. We discuss analogies between the disposition problem and the classical airline revenue management problem. We then develop single period and multi-period stochastic optimization models for the disposition problem. Analyzing these models, we show that the optimal allocation balances expected marginal profits across the disposition alternatives. A detailed numerical study reveals that a revenue management approach to the disposition problem significantly outperforms the current practice of focusing exclusively on high-margin options, and we identify conditions under which this improvement is the highest. We also show that the value recovered from the returned products critically depends on the coordination between forward and reverse supply chain decisions.remanufacturing;revenue management;onderdelen;revenues;spare parts inventory

A mathematical programming approach for supplier selection using Activity Based Costing.

Vendor selection is an important problem in today's competitive environment . Decisions involve the selection of vendors and the determination of order quantities to be placed with the selected vendors. In this research we develop a mathematical programming model for this purpose using an Activity Based Costing approach. The system computes the total cost of ownership, thereby increasing the objectivity in the selection process and giving the opportunity for different kinds of sensitivity analysis. Moreover, it allow the analyst to objectively evaluate alternative purchasing policies due to the underlying analytic and rigorous decision model.Activity based costing; Mathematical programming; Selection;

The structure of the optimal combined sourcing policy using capacity reservation and spot market with price uncertainty

This contribution focuses on the cost-effective management of the combined use of two procurement options: the short-term option is given by a spot-market with random price, whereas the long-term alternative is characterized by a multi period capacity reservation contract with fixed purchase price, reservation level and capacity reservation cost. Considering a multiperiod problem with stochastic demand, the structure of the optimal combined purchasing policy is derived using stochastic dynamic programming.Capacity reservation, spot market, purchasing policy, supply contracts, stochastic inventory control

Optimal acquisition policy for a supply network with discount schemes and uncertain demands.

This study uses a mathematical programming approach in which a series of Mixed Integer Non-Linear Programming (MINLP) models are developed to represent a supply network for a manufacturer dealing with various quantity or volume discount schemes from suppliers, as well as incorporating uncertain product demands that follow Normal distributions. Furthermore, the manufacturer\u27s optimal acquisition policy and production level are obtained simultaneously by solving the models with an objective of maximizing the expected value of the manufacturer\u27s profit. Although complicated by the employment of an integration function, the mathematical models are solved by a GAMS program with integrated SBB, CONOPT, MINOS, and SNOPT solvers working in collaboration. This research is one of the few studies in this field to use commercial optimization software for solving such complex mathematical models. The MINLP models and the GAMS solution program are applied in two real-world cases, and the preliminary results justify the capabilities of both the mathematical models and the GAMS solution program. Numerical analysis supports the managerial implications regarding the acquisition policy, and the comparison between the quantity discount and the volume discount. (Abstract shortened by UMI.)Dept. of Industrial and Manufacturing Systems Engineering. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2006 .M3. Source: Masters Abstracts International, Volume: 45-01, page: 0438. Thesis (M.A.Sc.)--University of Windsor (Canada), 2005