A general framework for cooperation under uncertainty

In this paper, we introduce a general framework for situations with decision making under uncertainty and cooperation possibilities. This framework is based upon a two stage stochastic programming approach. We show that under relatively mild assumptions the associated cooperative games are totally balanced. Finally, we consider several example situations.     

Job scheduling, cooperation, and control

This paper studies one machine job scheduling situations where clients can have more than one job to be processed and where a job can be of interest for different players. Corresponding cooperative games are introduced and a result on balancedness is provided.     

Trade-off between sample size and accuracy: Case of measurements under interval uncertainty

In many practical situations, we are not satisfied with the accuracy of the existing measurements. There are two possible ways to improve the measurement accuracy:

• First, instead of a single measurement, we can make repeated measurements; the additional information coming from these additional measurements can improve the accuracy of the result of this series of measurements.

• Second, we can replace the current measuring instrument with a more accurate one; correspondingly, we can use a more accurate (and more expensive) measurement procedure provided by a measuring lab – e.g., a procedure that includes the use of a higher quality reagent.

In general, we can combine these two ways, and make repeated measurements with a more accurate measuring instrument. What is the appropriate trade-off between sample size and accuracy? This is the general problem that we address in this paper.     

Fuzzy linear programming under interval uncertainty based on IFS representation

The equivalence between the interval-valued fuzzy set (IVFS) and the intuitionistic fuzzy set (IFS) is exploited to study linear programming problems involving interval uncertainty modeled using IFS. The non-membership of IFS is constructed with three different viewpoints viz., optimistic, pessimistic, and mixed. These constructions along with their indeterminacy factors result in S-shaped membership functions in the fuzzy counterparts of the intuitionistic fuzzy linear programming models. The solution methodology of Yang et al. [45], and its subsequent generalization by Lin and Chen [33] are used to compute the optimal solutions of the three fuzzy linear programming models.     

Majority voting leads to unanimity

We consider a situation where society decides, through majority voting in a secret ballot, between the alternatives of ‘reform’ and ‘status quo’. Reform is assumed to create a minority of winners, while being efficient in the Kaldor–Hicks sense. We explore the consequences of allowing binding transfers between voters conditional on the chosen alternative. In particular, we establish conditions under which the winners wish to compensate all losers, thus leading to unanimity for reform, rather than compensating some losers to form a non-maximal majority. The analysis employs concepts from cooperative game theory.      

Generalized linear fractional programming under interval uncertainty

Data in many real-life engineering and economical problems suffer from inexactness. Herein we assume that we are given some intervals in which the data can simultaneously and independently perturb. We consider a generalized linear fractional programming problem with interval data and present an efficient method for computing the range of optimal values. The method reduces the problem to solving from two to four real-valued generalized linear fractional programs, which can be computed in polynomial time using an appropriate interior point method solver.     

Two Game Models for Cooperation with Implicit Noncooperation

We propose two flexible game models to represent and analyze cases that cannot be modeled by current game models. One is called sharing creditability game (SCG) and the other is called bottomline game (BLG). The new models transform cooperative games into new games that incorporate auxiliary information (noncooperative in nature) usually neglected in previous theories. The new games will be solved only by traditional noncooperative game theory. When the new solutions are applied to the original games, the solutions can reflect the auxiliary information in addition to the original objectives of the decision makers or players. Generally, the new solutions are different from the cooperative and the noncooperative solutions of the original games. Existing transferable utility (TU) games and noncooperative games will coincide with special cases of the two new game models. Using SCG and BLG, the prisoner’s dilemma can be reformulated and a richer set of decisions can be considered for the players. The two new game models have potential applications in military and socioeconomic situations.This research was partly funded by the College Engineering, Ohio State University.     

On shortest path games

A class of cooperative TU-games arising from shortest path problems is introduced and analyzed. Some conditions under which a shortest path game is balanced are obtained. Also an axiomatic characterization of the Shapley value for this class of games is provided.     

A Chebyshev interval method for nonlinear dynamic systems under uncertainty

This paper proposes a new interval analysis method for the dynamic response of nonlinear systems with uncertain-but-bounded parameters using Chebyshev polynomial series. Interval model can be used to describe nonlinear dynamic systems under uncertainty with low-order Taylor series expansions. However, the Taylor series-based interval method can only suit problems with small uncertain levels. To account for larger uncertain levels, this study introduces Chebyshev series expansions into interval model to develop a new uncertain method for dynamic nonlinear systems. In contrast to the Taylor series, the Chebyshev series can offer a higher numerical accuracy in the approximation of solutions. The Chebyshev inclusion function is developed to control the overestimation in interval computations, based on the truncated Chevbyshev series expansion. The Mehler integral is used to calculate the coefficients of Chebyshev polynomials. With the proposed Chebyshev approximation, the set of ordinary differential equations (ODEs) with interval parameters can be transformed to a new set of ODEs with deterministic parameters, to which many numerical solvers for ODEs can be directly applied. Two numerical examples are applied to demonstrate the effectiveness of the proposed method, in particular its ability to effectively control the overestimation as a non-intrusive method.     

On characterization of the core of lane covering games via dual solutions

The lane covering game (LCG) is a cooperative game where players cooperate to reduce the cost of cycles that cover their required lanes on a network. We discuss the possibilities/impossibilities of a complete characterization of the core via dual solutions in LCGs played among a collection of shippers, each with a number of service requirements along some lanes, and show that such a complete characterization is possible if each shipper has at most one service requirement.     

Estimating sample mean under interval uncertainty and constraint on sample variance

Traditionally, practitioners start a statistical analysis of a given sample x₁, … , x_n by computing the sample mean E and the sample variance V. The sample values x_i usually come from measurements. Measurements are never absolutely accurate and often, the only information that we have about the corresponding measurement errors are the upper bounds Δ_i on these errors. In such situations, after obtaining the measurement result , the only information that we have about the actual (unknown) value x_i of the ith quantity is that x_i belongs to the interval . Different values x_i from the corresponding intervals lead, in general, to different values of the sample mean and sample variance. It is therefore desirable to find the range of possible values of these characteristics when x_i ∈ x_i.Often, we know that the values x_i cannot differ too much from each other, i.e., we know the upper bound V₀ on the sample variance V : V ? V₀. It is therefore desirable to find the range of E under this constraint. This is the main problem that we solve in this paper.     

区间合作对策在增广系统上的区间Shapley值

给出了区间合作对策在增广系统上的定义,并利用相应的公理体系及区间数运算的性质,构造出区间合作对策在增广系统上的区间Shapley值,论证了当对策为区间凸对策时的区间Shapley值的唯一性,且探讨了该区间Shapley值的一些性质.最后通过算例来说明在此类区间合作对策上所提方法的实用性与有效性.     

A multi-agent inventory problem with general transportation costs

This paper addresses the cost allocation problem that arises from an inventory system with multiple item and several agents that place joint orders according to an EOQ policy. In this setting, the cost per a new order has two components: a fixed cost and a variable cost. We assume that the variable part is given by a general function, not necessarily additive. We obtain the optimal policy and we evaluate some proposals of allocation rule for the ordering costs.     

Sequencing games with repeated players

Two classes of one machine sequencing situations are considered in which each job corresponds to exactly one player but a player may have more than one job to be processed, so called RP(repeated player) sequencing situations. In max-RP sequencing situations it is assumed that each player’s cost function is linear with respect to the maximum completion time of his jobs, whereas in min-RP sequencing situations the cost functions are linear with respect to the minimum completion times. For both classes, following explicit procedures to go from the initial processing order to an optimal order for the coalition of all players, equal gain splitting rules are defined. It is shown that these rules lead to core elements of the associated RP sequencing games. Moreover, it is seen that min-RP sequencing games are convex. We thank two referees for their valuable suggestions for improvement. Financial support for P. Calleja has been given by the Ministerio de Educación y Ciencia and FEDER under grant SEJ2005-02443/ECON, and by the Generalitat de Catalunya through a BE grant from AGAUR and grant 2005SGR00984.     

k-边覆盖对策及其核心

本文针对从图的k-边覆盖问题引出的合作对策模型，利用线性规划对偶理论得到了其核心非空的一个充分条件和构造核心分配的多项式时间算法，并将这一结果推广到了一般的k-集合覆盖对策模型中．     

Pooling of spare parts between multiple users: How to share the benefits?

Companies that maintain capital goods (e.g., airplanes or power plants) often face high costs, both for holding spare parts and due to downtime of their technical systems. These costs can be reduced by pooling common spare parts between multiple companies in the same region, but managers may be unsure about how to share the resulting costs or benefits in a fair way that avoids free riders. To tackle this problem, we study several players, each facing a Poisson demand process for an expensive, low-usage item. They share a stock point that is controlled by a continuous-review base stock policy with full backordering under an optimal base stock level. Costs consist of penalty costs for backorders and holding costs for on-hand stock. We propose to allocate the total costs proportional to players’ demand rates. Our key result is that this cost allocation rule satisfies many appealing properties: it makes all separate participants and subgroups of participants better off, it stimulates growth of the pool, it can be easily implemented in practice, and it induces players to reveal their private information truthfully. To obtain these game theoretical results, we exploit novel structural properties of the cost function in our (S − 1, S) inventory model.     

区间合成模糊对策

给出了一种新的合成模糊对策模型——区间合成模糊对策,研究了区间合成模糊对策的区间稳定集、区间核心、区间Shapley值、区间Banzhaf-Coleman势指标以及与子区间模糊对策的关系。区间合成模糊对策作为一种特殊的模糊数合成模糊对策,对于研究其它具有模糊数的模糊合成对策有一定的参考价值。     

Criterion function for accessibility,uncertainty problems in regional land-use planning

One objective in regional planning is the creation of communities with great accessibility. Thus we should plan the locations of inhabitants and the activities of the region so that the total accessibility will be maximized subject to some restrictions. This is a quadratic programming problem, which can be solved by quadratic programming techniques, but we cannot then take into account the uncertainties of the problem.In this paper a new criterion function is proposed for accessibility, uncertainty problems in regional land-use planning. It is derived from Hurwicz's generalized maximin principle. Many advantages are gained, for the planning problem is separated into linear programming problems, the uncertainties are taken into consideration as in game theory and the methods of parametric programming are available.A simplified problem of the populations of three town areas is studied and the method is generalized for problems of many activities and areas.     

不确定性环境下的经理人与股东合作博弈分析

针对不确定环境下的合作博弈问题，引入置信与丘奎特积分，给出了其均衡定义及求解方法。将上述方法应用到公司治理结构中，对经理人与股东在不确定性环境下的合作博弈进行求解，通过比较其均衡与非合作博弈均衡结果，说明该方法能够给双方带来更多的收益，从而实现帕累托改进。     

A note on maximal covering location games

In this note we introduce and analyze maximal covering location games. As the core may be empty, several sufficient conditions for core non-emptiness are presented. For each condition we provide an example showing that when the condition is not satisfied, core non-emptiness is not guaranteed.