The irreducible Core of a minimum cost spanning tree game

It is a known result that for a minimum cost spanning tree (mcst) game a Core allocation can be deduced directly from a mcst in the underlying network. To determine this Core allocation one only needs to determine a mcst in the network and it is not necessary to calculate the coalition values of the corresponding mcst game. In this paper we will deduce other Core allocations directly from the network, without determining the corresponding mcst game itself: we use an idea of Bird (cf. [4]) to present two procedures that determine a part of the Core (called the Irreducible Core) from the network.     

On the core of the minimum cost steiner tree game in networks

A cost allocation problem arising from the Steiner Tree (ST) problem in networks is analyzed. This cost allocation problem is formulated as a cost cooperative game in characteristic function form, referred to as theST-game. The class ofST games generalizes the class of minimum cost spanning tree games which were used in the literature to analyze a variety of cost allocation problems. In general, the core of anST-game may be empty. We construct an efficient Core Heuristic to compute a good lower bound on the maximum fraction of the total cost that can be distributed among users while satisfying the core constraints. Based on the Core Heuristic, we also provide a sufficient condition for a givenST not to be optimal for the linear programming relaxation of an integer programming formulation of theST problem. The Core Heuristic was implemented and tested on 76 data sets from the literature (Wong's, Aneja's and Beasley's Steiner tree problems). Core points were found for 69 of these cases, and points close to the core were computed in the others.     

最小费用k度限制树对策

本在Glover—Klingman算法及最小费用支撑树对策的基础上，讨论了最小费用k度限制树对策问题．利用威胁、旁支付理论制订了两种规则，并利用优超、策略等价理论分别给出了在这两种规则下最小费用k度限制树对策核心中的解，从而证明了在这两种规则下其核心非空．     

Merge-proofness in minimum cost spanning tree problems

In the context of cost sharing in minimum cost spanning tree problems, we introduce a property called merge-proofness. This property says that no group of agents can be better off claiming to be a single node. We show that the sharing rule that assigns to each agent his own connection cost (the Bird rule) satisfies this property. Moreover, we provide a characterization of the Bird rule using merge-proofness.     

Opportune moment strategies for a cost spanning tree game

Cost spanning tree problems concern the construction of a tree which provides a connection with the source for every node of the network. In this paper, we address cost sharing problems associated to these situations when the agents located at the nodes act in a non-cooperative way. A class of strategies is proposed which produce minimum cost spanning trees and, at the same time, are strong Nash equilibria for a non-cooperative game associated to the problem. They are also subgame perfect Nash equilibria.     

Truth-telling and Nash equilibria in minimum cost spanning tree models

In this paper we consider the minimum cost spanning tree model. We assume that a central planner aims at implementing a minimum cost spanning tree not knowing the true link costs. The central planner sets up a game where agents announce link costs, a tree is chosen and costs are allocated according to the rules of the game. We characterize ways of allocating costs such that true announcements constitute Nash equilibria both in case of full and incomplete information. In particular, we find that the Shapley rule based on the irreducible cost matrix is consistent with truthful announcements while a series of other well-known rules (such as the Bird-rule, Serial Equal Split, and the Proportional rule) are not.     

The optimistic <Emphasis Type="Italic">TU</Emphasis> game in minimum cost spanning tree problems

We associate an optimistic TU game with each minimum cost spanning tree problem. We define the worth of a coalition S as the cost of connecting agents in S to the source assuming that agents in N\S are already connected to the source, and agents in S can connect through agents in N\S. We study the Shapley value of this new game. We thank Hervé Moulin, William Thomson, and two referees for helpful comments. Financial support from the Ministerio de Ciencia y Tecnologia and FEDER through grant SEJ2005-07637-c02-01 is gratefully acknowledged.     

The folk solution and Boruvka’s algorithm in minimum cost spanning tree problems

Boruvka’s algorithm, which computes a minimum cost spanning tree, is used to define a rule to share the cost among the nodes (agents). We show that this rule coincides with the folk solution, a very well-known rule of this literature.     

A generalization of obligation rules for minimum cost spanning tree problems

Tijs et al. [23] introduce the family of obligation rules for minimum cost spanning tree problems. We give a generalization of such family. We prove that our family coincides with the set of rules satisfying an additivity property and a cost monotonicity property. We also provide two new characterizations for the family of obligation rules using the previous properties. In the first one, we add a property of separability; and in the second one, we add core selection.     

On the core and nucleolus of minimum cost spanning tree games

We develop two efficient procedures for generating cost allocation vectors in the core of a minimum cost spanning tree (m.c.s.t.) game. The first procedure requires O(n ²) elementary operations to obtain each additional point in the core, wheren is the number of users. The efficiency of the second procedure, which is a natural strengthening of the first procedure, stems from the special structure of minimum excess coalitions in the core of an m.c.s.t. game. This special structure is later used (i) to ease the computational difficulty in computing the nucleolus of an m.c.s.t. game, and (ii) to provide a geometric characterization for the nucleolus of an m.c.s.t. game. This geometric characterization implies that in an m.c.s.t. game the nucleolus is the unique point in the intersection of the core and the kernel. We further develop an efficient procedure for generating fair cost allocations which, in some instances, coincide with the nucleolus. Finally, we show that by employing Sterns' transfer scheme we can generate a sequence of cost vectors which converges to the nucleolus. Part of this research was done while the author was visiting the Department of Operations Research at Stanford University. This research was partially supported by Natural Sciences and Engineering Research Council Canada Grant A-4181.     

An exact solution framework for the minimum cost dominating tree problem

The minimum cost dominating tree problem is a recently introduced NP-hard problem, which consists of finding a tree of minimal cost in a given graph, such that for every node of the graph, the node or one of its neighbours is in the tree. We present an exact solution framework combining a primal–dual heuristic with a branch-and-cut approach based on a transformation of the problem into a Steiner arborescence problem with an additional constraint. The effectiveness of our approach is evaluated on testbeds proposed in literature containing instances with up to 500 nodes. Our framework manages to solve all but four instances from literature to proven optimality within 3 h (most of them in a few seconds). We provide optimal solution values for 69 instances from literature for which the optimal solution was previously unknown.     

Realizing fair outcomes in minimum cost spanning tree problems through non-cooperative mechanisms

In the context of minimum cost spanning tree problems, we present a bargaining mechanism for connecting all agents to the source and dividing the cost among them. The basic idea is very simple: we ask each agent the part of the cost he is willing to pay for an arc to be constructed. We prove that there exists a unique payoff allocation associated with the subgame perfect Nash equilibria of this bargaining mechanism. Moreover, this payoff allocation coincides with the rule defined in Bergantiños and Vidal-Puga [Bergantiños, G., Vidal-Puga, J.J., 2007a. A fair rule in minimum cost spanning tree problems. Journal of Economic Theory 137, 326–352].     

A characterization of Kruskal sharing rules for minimum cost spanning tree problems

In Tijs et al. (Eur J Oper Res 175:121–134, 2006) a new family of cost allocation rules is introduced in the context of cost spanning tree problems. In this paper we provide the first characterization of this family by means of population monotonicity and a property of additivity.     

Obligation rules for minimum cost spanning tree situations and their monotonicity properties

We consider the class of Obligation rules for minimum cost spanning tree situations. The main result of this paper is that such rules are cost monotonic and induce also population monotonic allocation schemes. Another characteristic of Obligation rules is that they assign to a minimum cost spanning tree situation a vector of cost contributions which can be obtained as product of a double stochastic matrix with the cost vector of edges in the optimal tree provided by the Kruskal algorithm. It turns out that the Potters value (P-value) is an element of this class.     

“Optimistic” weighted Shapley rules in minimum cost spanning tree problems

We introduce optimistic weighted Shapley rules in minimum cost spanning tree problems. We define them as the weighted Shapley values of the optimistic game v⁺ introduced in Bergantiños and Vidal-Puga [Bergantiños, G., Vidal-Puga, J.J., forthcoming. The optimistic TU game in minimum cost spanning tree problems. International Journal of Game Theory. Available from: <http://webs.uvigo.es/gbergant/papers/cstShapley.pdf>]. We prove that they are obligation rules [Tijs, S., Branzei, R., Moretti, S., Norde, H., 2006. Obligation rules for minimum cost spanning tree situations and their monotonicity properties. European Journal of Operational Research 175, 121–134].     

The prize-collecting generalized minimum spanning tree problem

We introduce the prize-collecting generalized minimum spanning tree problem. In this problem a network of node clusters needs to be connected via a tree architecture using exactly one node per cluster. Nodes in each cluster compete by offering a payment for selection. This problem is NP-hard, and we describe several heuristic strategies, including local search and a genetic algorithm. Further, we present a simple and computationally efficient branch-and-cut algorithm. Our computational study indicates that our branch-and-cut algorithm finds optimal solutions for networks with up to 200 nodes within two hours of CPU time, while the heuristic search procedures rapidly find near-optimal solutions for all of the test instances.     

Colorings at minimum cost

We define by min_c∑_{u,v}∈E(G)|c(u)−c(v)| the min-costMC(G) of a graph G, where the minimum is taken over all proper colorings c. The min-cost-chromatic numberχ_M(G) is then defined to be the (smallest) number of colors k for which there exists a proper k-coloring c attaining MC(G). We give constructions of graphs G where χ(G) is arbitrarily smaller than χ_M(G). On the other hand, we prove that for every 3-regular graph G^′, χ_M(G^′)≤4 and for every 4-regular line graph G^″, χ_M(G^″)≤5. Moreover, we show that the decision problem whether χ_M(G)=k is -hard for k≥3.     

The minimum spanning tree problem with fuzzy costs

In this paper the minimum spanning tree problem in a given connected graph is considered. It is assumed that the edge costs are not precisely known and they are specified as fuzzy intervals. Possibility theory is applied to characterize the optimality of edges of the graph and to choose a spanning tree under fuzzy costs.