A principal–agent problem with heterogeneous demand distributions for a carbon capture and storage system

Mechanism design problems optimize contract offerings from a principal to different types of agents who have private information about their demands for a product or a service. We study the implications of uncertainty in agents’ demands on the principal’s contracts. Specifically, we consider the setting where agents’ demands follow heterogeneous distributions and the principal offers a menu of contracts stipulating quantities and transfer payments for each demand distribution. We present analytical solutions for the special case when there are two distributions each taking two discrete values, as well as a method for deriving analytical solutions from numerical solutions. We describe one application of the model in carbon capture and storage systems to demonstrate various types of optimal solutions and to obtain managerial insights.     

Paths to stability and uniqueness in two-sided matching markets

The deferred acceptance algorithm introduced by Gale and Shapley is a centralized algorithm, where a social planner solicits the preferences from two sides of a market and generates a stable matching. On the other hand, the algorithm proposed by Knuth is a decentralized algorithm. In this article, we discuss conditions leading to the convergence of Knuth’s decentralized algorithm. In particular, we show that Knuth’s decentralized algorithm converges to a stable matching if either the Sequential Preference Condition (SPC) holds or if the market admits no cycle. In fact, acyclicity turns out to be a special case of SPC. We then consider markets where agents may prefer to remain single rather than being matched with someone. We introduce a generalized version of SPC for such markets. Under this notion of generalized SPC, we show that the market admits a unique stable matching, and that Knuth’s decentralized algorithm converges. The generalized SPC seems to be the most general condition available in the literature for uniqueness in two-sided matching markets.     

The stability of the equilibrium outcomes in the admission games induced by stable matching rules

A stable matching rule is used as the outcome function for the Admission game where colleges behave straightforwardly and the students’ strategies are given by their preferences over the colleges. We show that the college-optimal stable matching rule implements the set of stable matchings via the Nash equilibrium (NE) concept. For any other stable matching rule the strategic behavior of the students may lead to outcomes that are not stable under the true preferences. We then introduce uncertainty about the matching selected and prove that the natural solution concept is that of NE in the strong sense. A general result shows that the random stable matching rule, as well as any stable matching rule, implements the set of stable matchings via NE in the strong sense. Precise answers are given to the strategic questions raised.     

Some remarks on the stable matching problem

The stable matching problem is that of matching two sets of agents in such a manner that no two unmatched agents prefer each other to their mates. We establish three results on properties of these matchings and present two short proofs of a recent theorem of Dubins and Freedman.     

Two-sided coalitional matchings

In a two-sided coalitional matching problem agents on each side of the market simultaneously form coalitions which then are matched to coalitions from the other market side. We assume that each agent has preferences over groups on his own market side and over groups on the opposite market side. These preferences are combined lexicographically as to examine how the existence of core stable partitions on the distinct market sides, the restriction of agents’ preferences over groups to strict orderings, and the extent to which individual preferences respect common rankings shape the existence of core stable coalitional matchings.     

On the invariance of male optimal stable matching

The stable matching problem is that of matching two sets of agents in such a manner that no two unmatched agents prefer each other to their actual partners under the matching. In this paper, we present a set of sufficient conditions on the preference lists of any given stable matching instance, under which the optimality of the original male optimal stable matching is still preserved.     

An interval-coefficient fuzzy binary linear programming,the solution,and its application under uncertainties

The common difficulty in solving a Binary Linear Programming (BLP) problem is uncertainties in the parameters and the model structure. The previous studies of BLP problems normally focus on parameter uncertainty or model structure uncertainty, but not on both types of uncertainties. This paper develops an interval-coefficient Fuzzy Binary Linear Programming (IFBLP) and its solution for BLP problems under uncertainties both on parameters and model structure. In the IFBLP, the parameter uncertainty is represented by the interval coefficients, and the model structure uncertainty is reflected by the fuzzy constraints and a fuzzy goal. A novel and efficient methodology is used to solve the IFLBP into two extreme crisp-coefficient BLPs, which are called the ‘best optimum model’ and the ‘worst optimum model’. The results of these two crisp-coefficient extreme models can bound all outcomes of the IFBLP. One of the contributions in this paper is that it provides a mathematical sound approach (based on some mathematical developments) to find the boundaries of optimal alpha values, so that the linearity of model can be maintained during the conversions. The proposed approach is applied to a traffic noise control plan to demonstrate its capability of dealing with uncertainties.     

Group activity selection problem with approval preferences

We consider a setting where one has to organize one or several group activities for a set of agents. Each agent will participate in at most one activity, and her preferences over activities depend on the number of participants in the activity. The goal is to assign agents to activities based on their preferences in a way that is socially optimal and/or stable. We put forward a general model for this setting, which is a natural generalization of anonymous hedonic games. We then focus on a special case of our model where agents’ preferences are binary, i.e., each agent classifies all pairs of the form ‘(activity, group size)’ into ones that are acceptable and ones that are not. We formulate several solution concepts for this scenario, and study them from the computational point of view, providing hardness results for the general case as well as efficient algorithms for settings where agents’ preferences satisfy certain natural constraints.     

Where do we stand on measures of uncertainty,ambiguity, fuzziness,and the like?

It is argued in this paper that the theory of fuzzy sets involves at least four fundamentally different types of uncertainty. Each of these types requires a measure by which the degree of uncertainty of that type can be determined.Two main categories of uncertainty are connected with the terms ‘vagueness’ (or ‘fuzziness’) and ‘ambiguity’. In general, vagueness is associated with the difficulty of making sharp or precise distinctions in the world. Ambiguity, on the other hand, is associated with one-to-many relations, i.e., situations with two or more alternatives that are left unspecified. While the concept of a fuzzy set represents a basic mathematical framework for dealing with vagueness, the concept of a fuzzy measure is a general framework for dealing with ambiguity.Several classes of measures of vagueness, usually referred to as measures of fuzziness, have been proposed in the literature. Each class is based on some underlying conception of the degree of fuzziness. A general set of requirements for measures of fuzziness is formulated, followed by an overview of the measures proposed in the literature.Measures of ambiguity are discussed within the framework of plausibility and belief measures. Although it does not cover all fuzzy measures, this framework is sufficiently broad for most practical purposes, and represents a generalization of both probability theory and possibility theory.It is argued that three complementary measures of ambiguity should be employed. One of them is obtained by generalizing the Hartley measure of uncertainty; it measures the degree of nonspecificity in individual situations described by the various belief and plausibility measures. The other two are obtained by generalizing the well known Shannon measure of uncertainty; they measure the degree of dissonance and the degree of confusion in evidence, respectively. Basic mathematical properties of these measures are overviewed.It is also argued that each of the four types of uncertainty measures, which are fundamentally different from each other, can be used for measuring structural (syntactic) information in the same sense as the Hartley and Shannon measures have been used in this respect. As such, these measures are potentially powerful tools for dealing with systems problems such as systems modelling, analysis, simplification, or design.     

多对一双方匹配市场中的最优化

在双方市场中定义的博弈概念，可以使市场同方参与者的收益同时达到最大．这种最优化存在的理论依据是选择匹配的稳定性．用博弈论的分析与证明方法研宄多对一双方匹配市场中的最优化．在替代偏好和LAD（Law of Aggregate Demend）偏好下，证明由企业作选择的选择函数一定是个稳定匹配，由工人做选择的选择函数也是一个稳定匹配．     

基于证据推理与最优指派策略的多属性单边匹配决策

针对匹配中某一方偏好失效的问题,提出一种基于证据推理和最优指派策略的单边匹配方法。一方主体采用多种数据类型描述由对方指定的多个属性信息;另一方给出关于各属性的权重信息;然后,使用证据推理组合规则递推合成多属性及权重信息,以此计算双方的匹配度。在此基础上,运用最优指派策略,建立匹配模型并求解得到匹配结果.实例表明该方法的可行性和有效性。     

Singleton core in many-to-one matching problems

We explore two necessary and sufficient conditions for the singleton core in college admissions problems. One is a condition on the colleges’ preference profiles, called acyclicity, and the other is a condition on their capacity vectors. We also study the implications of our acyclicity condition. The student-optimal stable matching is strongly efficient for the students, given an acyclic profile of the colleges’ preference relations. Even when the colleges’ true preference profile is acyclic, a college may be better off by misreporting its preference when the college-optimal stable mechanism is used.     

Random paths to pairwise stability in many-to-many matching problems: a study on market equilibration

This paper considers a decentralized process in many-to-many matching problems. We show that if agents on one side of the market have substitutable preferences and those on the other side have responsive preferences, then, from an arbitrary matching, there exists a finite path of matchings such that each matching on the path is formed by satisfying a blocking individual or a blocking pair for the previous matching, and the final matching is pairwise-stable. This implies that an associated stochastic process converges to a pairwise-stable matching in finite time with probability one, if each blocking individual or pair is satisfied with a positive probability at each period along the process.     

The path player game

We give an explicit PDE characterization for the solution of the problemof maximizing the utility of both terminal wealth and intertemporal consumption undermodel uncertainty. The underlying market model consists of a risky asset, whosevolatility and long-term trend are driven by an external stochastic factor process. Therobust utility functional is defined in terms of a HARA utility function with risk aversionparameter 0 < α < 1 and a dynamically consistent coherent risk measure, whichallows for model uncertainty in the distributions of both the asset price dynamics andthe factor process. Ourmethod combines recent results by Wittmüß (Robust optimizationof consumption with random endowment, 2006) on the duality theory of robustoptimization of consumption with a stochastic control approach to the dual problemof determining a ‘worst-case martingale measure’.     

不确定偏好序信息下考虑主体心理行为的双边匹配决策方法

针对基于不确定偏好序信息的双边匹配问题,本文提出了一种决策方法。给出了双边匹配和不确定偏好序的相关概念,同时给出了不确定偏好序信息下考虑主体心理行为的双边匹配问题描述;以每个主体给出的临界值作为其参照点,计算了每个主体给出的不确定偏好序相对于参照点的收益或损失;考虑到主体损失规避的心理行为特征,依据TODIM思想计算每个主体对另一方主体的益损值的感知价值;在此基础上,构建了求解该双边匹配问题的双目标优化模型,使用线性加权法将双目标优化模型转化为单目标优化模型,通过求解该单目标优化模型获得匹配结果;最后,通过IT服务外包中的供给方与需求方的双边匹配实例分析说明了所提方法的有效性。     

Binary operations and lattice structure for a model of matching with contracts

We consider a restricted model of many-to-one matching with contracts and we order the set of stable allocations according both to the unanimous-for-doctors partial ordering and Blair’s partial ordering for hospitals. We define two binary operations to calculate the least upper bound and greatest lower bound for each pair of elements of this set in a simple way. By using these operations, we show that the set of stable allocations has dual lattice structures, thus reflecting an expected counterposition of interests between both sides of the market.     

Criticality in Stochastic Networks

The common definition of ‘criticality’ in stochastic networks is insufficiently general, and often counter-intuitive. An alternative metric, ‘cruciality’ has been proposed. The combination of the common criticality metric and cruciality is shown to provide information about the ‘uncertainty impact’ and ‘controllable benefit’ in the network.     

Improving credit scoring by differentiating defaulter behaviour

We present a methodology for improving credit scoring models by distinguishing two forms of rational behaviour of loan defaulters. It is common knowledge among practitioners that there are two types of defaulters, those who do not pay because of cash flow problems (‘Can’t Pay’), and those that do not pay because of lack of willingness to pay (‘Won’t Pay’). This work proposes to differentiate them using a game theory model that describes their behaviour. This separation of behaviours is represented by a set of constraints that form part of a semi-supervised constrained clustering algorithm, constructing a new target variable summarizing relevant future information. Within this approach the results of several supervised models are benchmarked, in which the models deliver the probability of belonging to one of these three new classes (good payers, ‘Can’t Pays’, and ‘Won’t Pays’). The process improves classification accuracy significantly, and delivers strong insights regarding the behaviour of defaulters.     

On the contracts between doctors and rural hospitals

We prove that the set of doctors assigned to a hospital with unfilled positions is the same in all stable allocations for a many-to-one matching model with contracts where all hospitals have q-separable preferences. However, the characteristics of the relationships among these agents may differ from one stable allocation to another.     

One-to-many non-cooperative matching games

We study a strategic model of wage negotiations between firms and workers. First, we define the stability of an allocation in an environment where firms can employ more than one worker. Secondly, we develop a one-to-many non-cooperative matching game, which is an extension of Kamecke’s one-to-one non-cooperative matching game. The main result shows the equivalence between the stable allocations and the outcomes of the subgame equilibria in the matching game: for any stable allocation in this game there is a subgame perfect equilibrium which induces the allocation on the equilibrium path, and every subgame perfect equilibrium induces a stable allocation on the equilibrium path. Furthermore, as for the existence of a stable allocation, we argue that a stable allocation, as with a subgame perfect equilibrium, does not always exist, but it exists under some conditions, using Kelso and Crawford’s modelling.