A Continuous Review Inventory System with Lost Sales and Emergency Orders

We analyze a continuous review lost sales inventory system with two types of orders—regular and emergency. The regular order has a stochastic lead time and is placed with the cheapest acceptable supplier. The emergency order has a deterministic lead time is placed with a local supplier who has a higher price. The emergency order is not always filled since the supplier may not have the ability to provide the order on an emergency basis at all times. This emergency order has a higher cost per item and has a known probability of being filled. The total costs for this system are compared to a system without emergency placement of orders. This paper provides managers with a tool to assess when dual sourcing is cost optimal by comparing the single sourcing and dual sourcing models

Climate Effects of Carbon Taxes, Taking into Account Possible Other Future Climate Measures

Increasing fuel extraction costs and global temperatures make it likely that in the medium-term future, technological or political measures against global warming will be implemented. In assessments of current climate policy, possible medium-term future developments, such as backstop technologies, are largely neglected, but such developments may crucially affect policy impacts. If such measures are implemented, a carbon tax introduced now may mitigate climate change to greater effect than recent reflections along the lines of the Green Paradox would suggest. Notably, the weak and the strong version of the Green Paradox, related to current and longer-term emissions, may not materialise. Moreover, the tax may allow the demanding countries to extract part of the resource rent, further increasing its desirability.Climate change policy, greenhouse gas tax, carbon tax, Green Paradox, anticipation effects, exhaustible resources, fossil fuels market, backstop technology, uncertainty, resource rent.

Pricing in a duopoly with a lead time advantage

We analyze the price competition between two suppliers offering two different lead times and two different prices to a buyer. The buyer chooses its inventory replenishment policy in order to minimize its infinite-horizon average cost. In essence, the fast and expensive supplier is used only in emergencies, while the slow and cheap supplier receives the bulk of the orders. Thus, despite a higher price, the fast supplier is able to capture a part of the buyer's orders. We analyze the price competition between the asymmetric suppliers, where the market share of each supplier is derived from the buyer's inventory problem. We find equilibria that differ significantly from the Bertrand price-only competition. In particular, for some cost parameters, the fast supplier is able to charge a premium for faster delivery, and stay in business even with a higher production cost. We obtain in some cases closed-form formulas for the price difference in equilibrium. Hence, our results show that high cost suppliers may not be driven out of business if they can offer fast delivery.offshoring; dual sourcing;

Stochastic versus Deterministic Approach to Coordinated Supply Chain Scheduling

The purpose of this paper is to consider coordinated selection of supply portfolio and scheduling of production and distribution in supply chains under regional and local disruption risks. Unlike many papers that assume the all-or-nothing supply disruption pattern, in this paper, only the regional disruptions belong to the all-or-nothing disruption category, while for the local disruptions all disruption levels can be considered. Two biobjective decision-making models, stochastic, based on the wait-and-see approach, and deterministic, based on the expected value approach, are proposed and compared to optimize the trade-off between expected cost and expected service. The main findings indicate that the stochastic programming wait-and-see approach with its ability to handle uncertainty by probabilistic scenarios of disruption events and the much simpler expected value problem, in which the random parameters are replaced by their expected values, lead to similar expected performance of a supply chain under multilevel disruptions. However, the stochastic approach, which accounts for all potential disruption scenarios, leads to a more diversified supply portfolio that will hedge against a variety of scenarios

Supplier selection under disaster uncertainty with joint procurement

Master of ScienceDepartment of Industrial & Manufacturing Systems EngineeringJessica L. Heier StammHealth care organizations must have enough supplies and equipment on hand to adequately respond to events such as terrorist attacks, infectious disease outbreaks, and natural disasters. This is achieved through a robust supply chain system. Nationwide, states are assessing their current supply chains to identify gaps that may present issues during disaster preparedness and response. During an assessment of the Kansas health care supply chain, a number of vulnerabilities were identified, one of which being supplier consolidation. Through mergers and acquisitions, the number of suppliers within the health care field has been decreasing over the years. This can pose problems during disaster response when there is a surge in demand and multiple organizations are relying on the same suppliers to provide equipment and supplies. This thesis explores the potential for joint procurement agreements to encourage supplier diversity by splitting purchasing among multiple suppliers. In joint procurement, two or more customers combine their purchases into one large order so that they can receive quantity discounts from a supplier. This research makes three important contributions to supplier selection under disaster uncertainty. The first of these is the development of a scenario-based supplier selection model under uncertainty with joint procurement. This optimization model can be used to observe customer purchasing decisions in various scenarios while considering the probability of disaster occurrence. Second, the model is applied to a set of experiments to analyze the results when supplier diversity is increased and when joint procurement is introduced. This leads to the third and final contribution: a set of recommendations for health care organization decision makers regarding ways to increase supplier diversity and decrease the risk of disruption associated with disaster occurrence

Effective Multi-echelon Inventory Systems for Supplier Selection and Order Allocation

Successful supply chain management requires an effective sourcing strategy to counteract uncertainties in both the suppliers and demands. Therefore, determining a better sourcing policy is critical in most of industries. Supplier selection is an essential task within the sourcing strategy. A well-selected set of suppliers makes a strategic difference to an organization\u27s ability to reduce costs and improve the quality of its end products. To discover the cost structure of selecting a supplier, it is more interesting to further determine appropriate levels of inventory in each echelon for different suppliers. This dissertation focuses on the study of the integrated supplier selection, order allocation and inventory control problems in a multi-echelon supply chain. First, we investigate a non-order-splitting inventory system in supply chain management. In particular, a buyer firm that consists of one warehouse and N identical retailers procures a type of product from a group of potential suppliers, which may have different prices, ordering costs, lead times and have restriction on minimum and maximum total order size, to satisfy stochastic demand. A continuous review system that implements the order quantity, reorder point (Q, R) inventory policy is considered in the proposed model. The model is solved by decomposing the mixed integer nonlinear programming model into two sub-models. Numerical experiments are conducted to evaluate the model and some managerial insights are obtained with sensitivity analysis. In the next place, we extend the study to consider the multi-echelon system with the order-splitting policy. In particular, the warehouse acquisition takes place when the inventory level depletes to a reorder point R, and the order Q is simultaneously split among m selected suppliers. This consideration is important since it could pool lead time risks by splitting replenishment orders among multiple suppliers simultaneously. We develop an exact analysis for the order-splitting model in the multi-echelon system, and formulate the problem in a Mixed Integer Nonlinear Programming (MINLP) model. To demonstrate the solvability and the effectiveness of the model, we conduct several numerical analyses, and further conduct simulation models to verify the correctness of the proposed mathematical model

Global welfare effects of transgenic sugar beet

Although the EU is still in a quasi moratorium stage concerning GM crops, doors for GM crops in the sugar industry seem to open. Herbicide tolerant sugar beet could mean a boost for the sugar beet sector. The ex ante impact assessment shows a created welfare of 15 billion during 1996-2014. The rule of thumb found in ex post impact studies of a sharing out between downstream and upstream sector of 2/3 versus 1/3 is seems to be applicable to this case as well. The sugar beet sector and consumers worldwide are the winners while cane growers lose due to technology eroded world prices. The reform of the EU Common market organization for sugar in 2006 seems to create an incentive for innovation to efficient European sugar producers. Crowding out of inefficient producers could take place as was one of the goals of the reform.Crop Production/Industries, Research and Development/Tech Change/Emerging Technologies,

Stochastic Viability of Second Generation Biofuel Chains: Micro-economic Spatial Modeling in France

Within an overall project to assess the ability of the agricultural sector to contribute to bioenergy production, we set out here to examine the economic and technological viability of a bioenergy facility in an uncertain economic context, using the stochastic viability approach. We consider two viability constraints: the facility demand for lignocellulosic feedstock has to be satisfied each year and the associated supply cost has to be lower than de profitability threshold of the facility. We assess the viability probability of various supplying strategies consisting in contracting a given share of the feedstock demand with perennial dedicated crops at the initial time and then in making up each year with annual dedicated crops or wood. The demand constraints and agricultural prices scenarios over the time horizon are introduced in an agricultural and forest biomass supply model, which in turns determines the supply cost per MWh and computes the viability probabilities of the various contract strategies. A sensibility analysis to agricultural prices at initial time is performed. Results show that when they are around or under the median (of the 1993–2007 prices), the strategy consisting in contracting 100% of the feedstock supply with perennial dedicated crops is the best one.Biofuel, Biomass production, Spatial economics, Stochastic viability, Monte Carlo simulation, Resource /Energy Economics and Policy,