Cooperative Game Theory Approach Research Articles

Simulation-optimization model for non-point source pollution management in watersheds: Application of cooperative game theory

A new cooperative watershed management methodology is designed for developing an equitable and efficient Best Management Practice cost allocation among landowners in a watershed. The approach intends to control the total sediment yield in the watershed, considering landowners’ conflicting interests. Wet detention ponds, are considered as the only available options to the landowners. The quality of the storm water is evaluated by the Total Suspended Solid loading from the watersheds. The proposed methodology combines a watershed simulation model, named Soil Water Accounting Tool (SWAT), with an Ant Colony Optimization (ACO) module and the cooperative game theory approach. Integration of SWAT and ACO modules provide the best set of designs for any constraints on target sediment removal set forth by non-cooperative and cooperative behaviors of the stakeholders to participate in the coalition to minimize the total cost of management practice. Nash Bargaining Theory is used to investigate how the maximum saving on cost of the participating players in a coalition can be fairly allocated. The proposed method is illustrated by a hypothetical example. The results demonstrate the applicability of the methodology. For the hypothetical case example, the proposed methodology with grand coalition leads to approximately 48 percent cost saving.

Application of Cost Allocation Concepts of Game Theory Approach for Cost Sharing Process

Dissatisfaction among involved parties regarding the ways of cost allocation is ordinary in the joint ventures, since each party attempts to get more interest caused by making the coalition. Various cost allocation methods such as proportional methods, some methods in cooperative game theory approach and etc have been used for the purpose of cost sharing in the joint projects. In this study the Nucleolus, Shapley value and SCRB as the cost sharing concepts in game theory approach have been used to investigate their effectiveness in fairly joint cost allocation between parties involved in constructing the joint water supply system. Then the results derived from these methods have been compared with the results of the traditional proportional to population and demand methods. The results indicated that the proportional methods may not lead to a fairly cost allocation while the Nucleolus, SCRB and the Shapley value methods can establish adequate incentive for cooperation.

Cooperative game theory approach to allocating benefits of horizontal cooperation

Logistics costs in general, and transportation costs in particular, represent a large fraction of the operating costs of many companies. One way to try to reduce these costs is through horizontal cooperation among shippers. Thus, when the transportation needs of two or more companies are merged, their collective transportation requirements can be met at lower cost. The attainable cost savings are due to economies of scale, which translate into cheaper rates due to increased negotiation power, use of larger vehicles and bundling of shipments. In this paper, a linear model is presented and used to study the cost savings that different companies may achieve when they merge their transportation requirements. On the one hand, solving this optimization model for different collaboration scenarios allows testing and quantifying the synergies among different potential partners, thus identifying the most profitable collaboration opportunities. On the other, the problem of allocating the joint cost savings of the cooperation is tackled using cooperative game theory. The proposed approach is illustrated with an example in which different cooperative game solution concepts are compared. Extensive numerical experiments have also been carried out to gain insight into the properties of the corresponding cost savings game and the behavior of the different solution concepts.

Water Costs Allocation in Complex Systems Using a Cooperative Game Theory Approach

The management of complex water resource systems that address water service recovery costs and consider adequate contributions and priorities require methods that integrate technical, economic, environmental, social and legal aspects into a comprehensive framework. In Europe, the Water Framework Directive (WFD) 2000/60/EC recommends that the pricing politics in a river basin take into account the cost recovery and the economic sustainability of the water use. However, the current cost allocation methods do not consider the user’s willingness to pay and often do not permit a total cost recovery. Thus, a new approach is required that includes these requirements when defining water rates. This article presents a methodology to allocate water service costs in a water resource system among different users that attempts to fulfil the WFD requirements. The methodology is based on Cooperative Game Theory (CGT) techniques and on the definition of the related characteristic function using a mathematical optimisation approach. The CGT provides the instruments that are necessary to analyse situations that require a cost-sharing rule. The CGT approach can define efficient and fair solutions that provide the appropriate incentives among the parties involved. Therefore, the water system cost allocation has been valued as a game in which it is necessary to determine the right payoff for each player that is, in this case, a water user. To apply the CGT principles in a water resources system, the characteristic function needs to be defined and evaluated using an adequate modelling approach; in this study, it is evaluated using the optimisation model WARGI. (Sechi and Zuddas 2000). The so-called “core” represents the game-solution set. It represents the area of the admissible cost allocation values from which the boundaries on the cost values for each player can be supplied. Within the core lie all of the allocations that satisfy the principles of equity, fairness, justice, efficiency and that guarantee cost recovery. The core of a cooperative game can represent a useful instrument to define the water cost rates. Furthermore, it can be used as a valid support in water resource management to achieve the economic analysis required by the WFD. The methodology was applied to a multi-reservoir and multi-demand water system in Sardinia, Italy.

Cooperative institutions for sustainable common pool resource management: Application to groundwater

Beneficiaries of common pool resources (CPRs) may select available noncooperative and regulatory exogenous institutions for managing the resource, as well as cooperative management institutions. All these institutions may increase the long‐term gains, prolong the life of the resource, and help to escape the tragedy of the commons trap. Cooperative game theory approaches can serve as the backbone of cooperative CPR management institutions. This paper formulates and applies several commonly used cooperative game theoretic solution concepts, namely, the core, Nash‐Harsanyi, Shapley, and nucleolus. Through a numerical groundwater example, we show how CPR users can share the gains obtained from cooperation in a fair and efficient manner based on these cooperative solution concepts (management institutions). Although, based on their fairness rationales, various cooperative management institutions may suggest different allocations that are potentially acceptable to the users, these allocation solutions may not be stable as some users may find them unfair. This paper discusses how different methods, such as application of the plurality rule and power index, stability index, and propensity to disrupt concepts, can help identify the most stable and likely solutions for enforcing cooperation among the CPR beneficiaries. Furthermore, how the noncooperative managerial characteristics of the CPR users can affect the stability and acceptability of the different cooperative CPR management institutions is discussed, providing valuable policy insights for cooperative CPR management at community levels.

Data Replication in Cooperative Mobile Ad-Hoc Networks

The mobile computing environment provides many benefits such as ubiquitous access to computing but includes constraints on resources such as available bandwidth and battery life. Replication is a widely recognized method for balancing the demands of storage space with bandwidth and battery life. We propose a novel scheme that seeks to strategically balance these constrained resources through a cooperative game-theory approach for replication in a mobile environment. Our replication strategy relies on the cooperation of the nodes within the network to make replica caching decisions which are spatiotemporally local-optimal for the network from an energy and bandwidth conservation standpoint. In cooperative altruistic data replication, each node calculates the net global benefit, for caching a replica of the requested data, as the result data is returned from the responding node to the requesting node, where it determines the spatiotemporally local-optimal node for replicating the data item. Performance results from our research indicate that our scheme, CADR, improves the query response time by 25 and 45 %, mean hop count is improved by 26 and 46 %, query error is reduced by 30 and 48 %, while energy utilization is reduced 30 and 57 % when compared with both another game theoretic replication approach and standard cooperative caching respectively.

Information sharing in DEA: A cooperative game theory approach

In this paper, a cooperative DEA game is proposed based on the idea that different organizations can gain if they share data on the input consumption and output production of their processing units. A larger data sample allows a more complete description of the Production Possibility Set and, consequently, of the efficient frontier. However, since not all organizations will benefit in the same way, it is convenient to use cooperative game theory in order to share the benefits of the cooperation. The proposed cooperative DEA game is shown to be subadditive and balanced. Models for computing the τ-value of the game and checking its stability, taking into account the exponential number of coalitions that exist when the number of organizations is large, are also presented. The approach is illustrated with a dataset from the literature.

Fairness: A Challenge for the Distribution of Cooperation Gains in Value Chains

Most scientific publications on the subject of value chain management only analyze which structures, processes and actions can contribute to the creation of cooperation gains. How the distribution of cooperation gains that were collectively achieved can influence the stability of such a cooperation is often disregarded. The distributive justice or the fair distribution of collectively created cooperation gains is one of the most important ways to secure the stability of networks. This paper therefore presents a proposal for an operationalization of the fairness term from an economic perspective. This proposal is specific to the distribution of cooperation gains in networks of autonomously acting companies and takes a cooperative game theory approach as its basis. With the aid of the τ-value, it is shown how intuitive and vague associations of fairness can be substantiated to give a concrete distribution proposal that can be perceived and communicated as fair by gradually establishing rational or at least plausible assumptions.

Coordination of supply chains by option contracts: A cooperative game theory approach

Manufacturer–retailer supply chains commonly adopt a wholesale price mechanism. This mechanism, however, has often led manufacturers and retailers to situations of conflicts of interest. For example, due to uncertain market demand, retailers prefer to order flexibly from manufacturers so as to avoid incurring inventory costs and to be able to respond flexibly to market changes. Manufacturers, on the other hand, prefer retailers to place full orders as early as possible so that they can hedge against the risks of over- and under-production. Such conflicts between retailers and manufacturers can result in an inefficient supply chain. Motivated by this problem, we take a cooperative game approach in this paper to consider the coordination issue in a manufacturer–retailer supply chain using option contracts. Using the wholesale price mechanism as a benchmark, we develop an option contract model. Our study demonstrates that, compared with the benchmark based on the wholesale price mechanism, option contracts can coordinate the supply chain and achieve Pareto-improvement. We also discuss scenarios in which option contracts are selected according to individual supply chain members’ risk preferences and negotiating powers.

Capacity sharing in a network of independent factories: A cooperative game theory approach

Market changes, uncertainties and unpredictability characterize the market environment nowadays. The possibility to cooperate in a network allows companies to stay competitive. This paper proposes a game theory coordination mechanism for a network of independent plants; the approach is based on the OWEN's theorem properly simulated in order to investigate different performances in various environmental conditions. To support the network and face the capacity sharing issue, a Multi-Agent Architecture has been specifically developed. The simulation results show that the proposed mechanism could be considered a valid alternative to the more usual negotiation approaches in several market conditions. The plants gain considerable benefits by participating in a network supported by the cooperative mechanism proposed.

A Resource Allocation Algorithm in Cognitive Radio Networks Based on Cooperative Game Theory Approach

In cognitive networks, the parameters of radios were adapted to achieve end-to-end or network objectives such as spectral or energy efficiency, reliability, or throughput maximization. In these networks, the licensed spectrum and dynamic spectrum sharing based on opportunistic communication play an important role of resource allocation. Since the resource allocation networks always cooperate and coexist in cognitive, Game theory has been employed to analysis that. In really case, the cooperator only have partial or no information concerning in advance to making decision. However, the current game theory models in cognitive radio networks always regard they have enough information. In this paper, we take Incomplete Information into account and propose an algorithm base on game theory to resource allocation. Compare traditional algorithms, this one can improve the in the cognitive radio networks as the simulations showing.

Incentivizing peer-assisted services

A new generation of content delivery networks for live streaming, video on demand, and software updates takes advantage of a peer-to-peer architecture to reduce their operating cost. In contrast with previous uncoordinated peer-to-peer schemes, users opt-in to dedicate part of the resources they own to help the content delivery, in exchange for receiving the same service at a reduced price. Such incentive mechanisms are appealing, as they simplify coordination and accounting. However, they also increase a user's expectation that she will receive a fair price for the resources she provides. Addressing this issue carefully is critical in ensuring that all interested parties--including the provider--are willing to participate in such a system, thereby guaranteeing its stability. In this paper, we take a cooperative game theory approach to identify the ideal incentive structure that follows the axioms formulated by Lloyd Shapley. This ensures that each player, be it the provider or a peer, receives an amount proportional to its contribution and bargaining power when entering the game. In general, the drawback of this ideal incentive structure is its computational complexity. However, we prove that as the number of peers receiving the service becomes large, the Shapley value received by each player approaches a fluid limit. This limit follows a simple closed form expression and can be computed in several scenarios of interest: by applying our technique, we show that several peer-assisted services, deployed on both wired and wireless networks, can benefit from important cost and energy savings with a proper incentive structure that follows simple compensation rules.

Comparison between Financial Theory and Cooperative Game Theory in Risk Capital Allocation

We compare two prominent approaches to capital allocation in insurance firms. The financial theory approach includes Merton and Perold (1993) and Myers and Read (2001). The cooperative game theory approach utilizes concepts such as the Shapley value and the Aumann-Shapley value. We argue that, when an entire division is added or when the effect of a decision is discrete, the Shapley value approach provides an improvement over the Merton and Perold approach in that it properly accounts for the order in which divisions are added, and resoles the unallocated capital problem. When the effect of a decision is continuous, we show that the Auman-Shapley value approach not only provides game theoretic support for, but also conceptually extends, the Myers and Read approach.

Multi-agent team cooperation: A game theory approach

The main goal of this work is to design a team of agents that can accomplish consensus over a common value for the agents’ output using cooperative game theory approach. A semi-decentralized optimal control strategy that was recently introduced by the authors is utilized that is based on minimization of individual cost using local information. Cooperative game theory is then used to ensure team cooperation by considering a combination of individual cost as a team cost function. Minimization of this cost function results in a set of Pareto-efficient solutions. Among the Pareto-efficient solutions the Nash-bargaining solution is chosen. The Nash-bargaining solution is obtained by maximizing the product of the difference between the costs achieved through the optimal control strategy and the one obtained through the Pareto-efficient solution. The latter solution results in a lower cost for each agent at the expense of requiring full information set. To avoid this drawback some constraints are added to the structure of the controller that is suggested for the entire team using the linear matrix inequality (LMI) formulation of the minimization problem. Consequently, although the controller is designed to minimize a unique team cost function, it only uses the available information set for each agent. A comparison between the average cost that is obtained by using the above two methods is conducted to illustrate the performance capabilities of our proposed solutions.

Property appraisal in high-rises: A cooperative game theory approach

The construction of the higher stories in a building is utterly contingent upon the construction of the lower ones, while the construction of lower stories does not require the construction of the higher ones. This rationale underlies our adoption of a cooperative game theory methodology for examining the value of units based on the cost approach of land appraisal. Particularly, we propose the Shapley value solution to examine the allocation of the land and construction cost among the stories of the building. We explore the allocation mechanism and derive several closed-form properties by which the value pattern of stories in a building is rationalized. The proposed cost allocation may, among other things, generate values when comparable market prices are unobservable (consistent with the cost approach); may be used by courts in order to compute compensations in cases of disputes regarding expansions and redevelopments of existing structures among co-owners; and may determine the rent cost allocation in an organization with several profit centers located on different floors of a building.

Comparison between Financial Theory and Cooperative Game Theory in Risk Capital Allocation

We compare two prominent approaches to capital allocation in insurance firms. The financial theory approach includes Merton and Perold (1993) and Myers and Read (2001). The cooperative game theory approach utilizes concepts such as the Shapley value and the Aumann-Shapley value. We argue that, when an entire division is added or when the effect of a decision is discrete, the Shapley value approach provides an improvement over the Merton and Perold approach in that it properly accounts for the order in which divisions are added, and resoles the unallocated capital problem. When the effect of a decision is continuous, we show that the Auman-Shapley value approach not only provides game theoretic support for, but also conceptually extends, the Myers and Read approach.

English Voting Theorists of the 19th Century: An Early Cooperative Game Theory Approach

Sino ad oggi gli economisti, con l’eccezione di Duncan Black, non hanno prestato molta attenzione agli studi sulla rappresentanza proporzionale, un tema che ha suscitato molto interesse in Inghilterra nel secolo scorso. In questo scritto si analizzano le indagini più importanti di quel periodo, mostrando le loro relazioni con la teoria dei giochi cooperativi. Alla base, infatti, di queste indagini vi era il proposito di affrontare con un qualche criterio di equità il problema delle divergenze di opinione tra individui aumentando il valore del voto delle minoranze, in modo da incoraggiare i votanti ad esercitare i loro diritti in modo responsabile. Un limite individuato da questi studi è che i governi di coalizione eletti con il criterio della rappresentanza proporzionale tendono ad avere una vita più breve di quelli conseguenti alla regola maggioritaria. Si tratta, tuttavia, di una critica che si può considerare valida soltanto se l’obiettivo è quello di avere un governo dotato di forte potere. Nel complesso, la caratteristica più significativa della rappresentanza proporzionale individuata da questi studi è costituita dal riconoscimento che una votazione è un giuoco co operativo e che le dimensioni di una coalizione efficace dipendono dalle regole di voto.

Game theory approach for multiobjective structural optimization

The concept of Pareto-optimal solution is discussed in the context of a multiobjective structural optimization problem and the commonly used methods of generating Pareto-optimal solutions are indicated. The graphical interpretations of the non-cooperative and cooperative game theory approaches are presented for a two-criteria optimization problem. The relationship between Pareto-optimal solutions and game theory is described. A computational procedure is developed for solving a general multiobjective optimization problem using cooperative game theory. The procedure is illustrated with two numerical examples.