Sequencing games without initial order

In this note we study uncertainty sequencing situations, i.e., one-machine sequencing situations in which no initial order is specified. We associate cooperative games with these sequencing situations, study their core, and provide links with the classic sequencing games introduced by Curiel et al. (Eur J Oper Res 40:344–351, 1989). Moreover, we propose and characterize two simple cost allocation rules for uncertainty sequencing situations with equal processing times.     

Cooperative games of choosing partners and forming coalitions in the marketplace

Two games of interacting between a coalition of players in a marketplace and the residual players acting there are discussed, along with two approaches to fair imputation of gains of coalitions in cooperative games that are based on the concepts of the Shapley vector and core of a cooperative game. In the first game, which is an antagonistic one, the residual players try to minimize the coalition's gain, whereas in the second game, which is a noncooperative one, they try to maximize their own gain as a coalition. A meaningful interpretation of possible relations between gains and Nash equilibrium strategies in both games considered as those played between a coalition of firms and its surrounding in a particular marketplace in the framework of two classes of n-person games is presented. A particular class of games of choosing partners and forming coalitions in which models of firms operating in the marketplace are those with linear constraints and utility functions being sums of linear and bilinear functions of two corresponding vector arguments is analyzed, and a set of maximin problems on polyhedral sets of connected strategies which the problem of choosing a coalition for a particular firm is reducible to are formulated based on the firm models of the considered kind.     

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．     

Kinetics of cooperative conformational transitions of lineal biopolymers

Cooperative conformational transitions of proteins and nucleic acids are of decisive importance to many processes of molecular biology, and particularly to their regulation. They proceed via numerous interdependent elementary processes, and their kinetics are therefore often complicated. They are frequently also very fast. However, kinetic analyses can be carried out by chemical relaxation methods. The theoretical interpretation is comparatively simple in the case of linear biopolymers. When the linear Ising model extended for kinetics was applied to model peptides and polynucleotides, it provided an insight into the fundamental principles of cooperative transformations.     

On the population monotonicity of independent set games

An independent set game is a cooperative game dealing with profit sharing in the maximum independent set problem. A population monotonic allocation scheme is a rule specifying how to share the profit of each coalition among its participants such that every participant is better off when the coalition expands. In this paper, we provide a necessary and sufficient characterization for independent set games admitting population monotonic allocation schemes. Moreover, our characterization can be verified efficiently.     

A new approach to agglomeration problems

In this paper, we study a location problem with positive externalities. We define a new transferable utility game, considering there is no restriction on the transfer of benefits between firms. We prove that the core of this game is non-empty, provide an expression for it, and an axiomatic characterization. We also study several core allocations, selected by means of a certain bankruptcy problem.     

Cooperative Competition Clustering for Gene Selection

Clustering analysis of data from DNA microarray hybridization studies is an essential task for identifying biologically relevant groups of genes. Attribute cluster algorithm (ACA) has provided an attractive way to group and select meaningful genes. However, ACA needs much prior knowledge about the genes to set the number of clusters. In practical applications, if the number of clusters is misspecified, the performance of the ACA will deteriorate rapidly. We propose the Cooperative Competition Cluster Algorithm (CCCA) in this paper. In the algorithm, we assume that both cooperation and competition exist simultaneously between clusters in the process of clustering. By using this principle of Cooperative Competition, the number of clusters can be found in the process of clustering. Experimental results on a synthetic and gene expression data are demonstrated. The results show that CCCA can choose the number of clusters automatically and get excellent performance with respect to other competing methods.     

Joint optimal fair cooperative spectrum sensing and transmission in cognitive radio

Since the sensing power consumption of cooperative spectrum sensing (CSS) will decrease the throughput of secondary users (SU) in cognitive radio (CR), a joint optimal model of fair CSS and transmission is proposed in this paper, which can compensate the sensing overhead of cooperative SUs. The model uses the periodic listen-before-transmission method, where each SU is assigned a portion of channel bandwidth, when the primary user (PU) is estimated to be free by the coordinator. Then, a joint optimization problem of local sensing time, number of cooperative SUs, transmission bandwidth and power is formulated, which can compensate the sensing overhead of cooperative SUs appropriately through choosing suitable compensating parameter. The proposed optimization problem can be solved by the Polyblock algorithm. Simulation results show that compared with the traditional model, the total system throughput of the fairness cooperation model decreases slightly, but the total throughput of the cooperative SUs improves obviously.