Judith B. Timmer

On three Shapley-like solutions for cooperative games with random payoffs

Abstract.Three solution concepts for cooperative games with random payoffs are introduced. These are the marginal value, the dividend value and the selector value. Inspiration for their definitions comes from several equivalent formulations of the Shapley value for cooperative TU games. An example shows that the equivalence is not preserved since these solutions can all be different for cooperative games with random payoffs. Properties are studied and a characterization on a subclass of games is provided.

Robust dynamic cooperative games

Classical cooperative game theory is no longer a suitable tool for those situations where the values of coalitions are not known with certainty. We consider a dynamic context where at each point in time the coalitional values are unknown but bounded by a polyhedron. However, the average value of each coalition in the long run is known with certainty. We design “robust” allocation rules for this context, which are allocation rules that keep the coalition excess bounded while guaranteeing each player a certain average allocation (over time). We also present a joint replenishment application to motivate our model.

A note on NTU-convexity

Abstract. For cooperative games with transferable utility, convexity has turned out to be an important and widely applicable concept. Convexity can be defined in a number of ways, each having its own specific attractions. Basically, these definitions fall into two categories, namely those based on a supermodular interpretation and those based on a marginalistic interpretation. For games with nontransferable utility, however, the literature mainly focuses on two kinds of convexity, ordinal and cardinal convexity, which both extend the supermodular interpretation. In this paper, we analyse three types of convexity for NTU games that generalise the marginalistic interpretation of convexity.

COLLECTING INFORMATION TO IMPROVE DECISION-MAKING

In this paper, we consider information collecting (IC) situations where an action taker in an uncertain situation can improve his action choices by gathering information from some players who are more informed about the situation. Then the problem of sharing the gains when cooperating with informants is tackled by constructing an appropriate game, the IC-game corresponding to the IC-situation. It turns out that the cone of IC-games, given a fixed set of players, coincides with the cone of 0-normalized monotonic games with a veto player. Also special classes of convex IC-games and big boss IC-games are considered, for which more is known about the solution concepts.

Supply Chain Collaboration

In the past, research in operations management focused on single-firm analysis. Its goal was to provide managers in practice with suitable tools to improve the performance of their firm by calculating optimal inventory quantities, among others. Nowadays, business decisions are dominated by the globalization of markets and increased competition among firms. Further, more and more products reach the customer through supply chains that are composed of independent firms. Following these trends, research in operations management has shifted its focus from single-firm analysis to multi-firm analysis, in particular to improving the efficiency and performance of supply chains under decentralized control. The main characteristics of such chains are that the firms in the chain are independent actors who try to optimize their individual objectives, and that the decisions taken by a firm do also affect the performance of the other parties in the supply chain. These interactions among firms’ decisions ask for alignment and coordination of actions. Therefore, game theory, the study of situations of cooperation or conflict among heterogenous actors, is very well suited to deal with these interactions. This has been recognized by researchers in the field, since there are an ever increasing number of papers that applies tools, methods and models from game theory to supply chain problems.

Information collecting situations and bi-monotonic allocation schemes

Abstract. This paper studies information collecting (IC) situations with the help of cooperative game theory. Relations are established between IC situations and IC games on one hand and information sharing (IS) situations and IS games on the other hand. Further, it is shown that IC games are convex combinations of so-called local games. Properties such as k-convexity and k-concavity are possessed by an IC game if all related local games have the respective properties. Special attention is paid to the classes of k-symmetric IC games and k-concave IC games. This last class turns out to consist of total big boss games. For the class of total big boss games a new solution concept is introduced: bi-monotonic allocation schemes. This solution takes the power of the big boss into account.

Cooperation and game-theoretic cost allocation in stochastic inventory models with continuous review

We study cooperation strategies for companies that continuously review their inventories and face Poisson demand. Our main goal is to analyze stable cost allocations of the joint costs. These are such that any group of companies has lower costs than the individual companies. If such allocations exist they provide an incentive for the companies to cooperate. We consider two natural cooperation strategies: (i) the companies jointly place an order for replenishment if their joint inventory position reaches a certain reorder level, and (ii) the companies reorder as soon as one of them reaches its reorder level. Numerical experiments for two companies show that the second strategy has the lowest joint costs. Under this strategy, the game-theoretical Shapley value and the distribution rule—a cost allocation in which the companies share the procurement cost and each pays its own holding cost—are shown to be stable cost allocations. These results also hold for situations with three companies.

Linear transformation of products: games and economies

In this paper, we introduce situations involving the linear transformation of products (LTP). LTP situations are production situations where each producer has a single linear transformation technique. First, we approach LTP situations from a (cooperative) game theoretical point of view. We show that the corresponding LTP games are totally balanced. By extending an LTP situation to one where a producer may have more than one linear transformation technique, we derive a new characterization of (nonnegative) totally balanced games: each totally balanced game with nonnegative values is a game corresponding to such an extended LTP situation. The second approach to LTP situations is based on a more economic point of view. We relate (standard) LTP situations to economies in two ways and we prove that the economies are standard exchange economies (with production). Relations between the equilibria of these economies and the cores of cooperative LTP games are investigated.

Semi-Infinite Assignment Problems and Related Games

Abstract. 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.

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.