Coordination mechanisms for inventory control in three-echelon serial and distribution systems

This paper is concerned with the coordination of inventory control in three-echelon serial and distribution systems under decentralized control. All installations in these supply chains track echelon inventories. Under decentralized control the installations will decide upon base stock levels that minimize their own inventory costs. In general these levels do not coincide with the optimal base stock levels in the global optimum of the chain under centralized control. Hence, the total cost under decentralized control is larger than under centralized control. To remove this cost inefficiency, two simple coordination mechanisms are presented: one for serial systems and one for distribution systems. Both mechanisms are initiated by the most downstream installation(s). The upstream installation increases its base stock level while the downstream installation compensates the upstream one for the increase of costs and provides it with a part of its gain from coordination. It is shown that both coordination mechanisms result in the global optimum of the chain being the unique Nash equilibrium of the corresponding strategic game. Furthermore, all installations agree upon the use of these mechanisms because they result in lower costs per installation. The practical implementation of these mechanisms is discussed

Correction and additional analysis of "Supply chain coordination by revenue sharing contracts" by Giannoccaro and Pontrandolfo

This work corrects the errors in the work of Giannoccaro and Pontrandolfo (in press) on revenue sharing contracts in three-stage serial supply chains. Further, an additional analysis of their model is provided. It is shown that revenue sharing contracts are not always an appropriate coordination mechanism

Conditions for rank reversal in supplier selection

Supplier selection is the process of selecting the best bid among a number of bids submitted by different suppliers. The bids are all evaluated against a set of predetermined criteria. If there are more criteria, the bids receive a score on each criterion. The bid with the best total score over all criteria wins. A common and sometimes even mandatory scoring rule per criterion is to assign the maximum score to the best bid on that criterion and to relate all other scores on that criterion to that best bid. This is a form of relative scoring, which is well known to open the way to rank reversal, the phenomenon that the ranking between two bidders is reversed. This may happen when, for example, an additional bid is taken into account, or when one of the original bids is removed. In supplier selection this is especially harmful when the rank reversal involves the winning bid. In this paper we investigate under which conditions rank reversal with regard to the winning bid can occur

Cost sharing of cooperating queues in a Jackson network

We consider networks of queues in which the independent operators of individual queues may cooperate to reduce the amount of waiting. More specifically, we focus on Jackson networks in which the total capacity of the servers can be redistributed over all queues in any desired way. If we associate a cost to waiting that is linear in the queue lengths, it is known from the literature how the operators should share the available service capacity to minimize the long run total cost. This paper deals with the question whether or not (the operators of) the individual queues will indeed cooperate in this way, and if so, how they could share the cost in the new situation such that each operator never pays more than his own cost without cooperation. For the particular case of a tandem network with two or three nodes it is known from previous work that cooperation is indeed beneficial, but for larger tandem networks and for general Jackson networks this question was still open. The main result of this paper gives for any Jackson network an explicit cost allocation that is beneficial for all operators. The approach we use also works for other cost functions, such as the server utilization

Semi-infintite assignment problems and related games

In this paper we look at semi-infinite assignment problems. These are situations where a finite set of agents of one type has to be assigned to an infinite set of agents of another type. This has to be done in such a way that the total profit arising from these assignments is as large as possible. An infinite programming problem and its dual arise here, which we tackle with the aid of finite approximations. We prove that there is no duality gap and we show that the core of the corresponding game is nonempty. Finally, the existence of optimal assignments is discussed

Convexity in stochastic cooperative situations

This paper introduces a new model concerning cooperative situations in which the payoffs are modeled by random variables. We analyze these situations by means of cooperative games with random payoffs. Special attention is paid to three types of convexity, namely coalitional-merge, individual-merge and marginal convexity. The relations between these types are studied and in particular, as opposed to their deterministic counterparts for TU games, we show that these three types of convexity are not equivalent. However, all types imply that the core of the game is nonempty. Sufficient conditions on the preferences are derived such that the Shapley value, defined as the average of the marginal vectors, is an element of the core of a convex game