Coalition formation with local public goods and group-size effect

Many public goods that are provided by coalitions have a group-size effect. Namely, people prefer to consume a public good in a larger coalition. This paper studies local public goods games with anonymous and separable group-size effect. The core is nonempty when coalition feasible sets are monotonic and players’ preferences over public goods satisfy a condition called cardinal connectedness. Moreover, a core allocation consists of connected coalitions.     

Warm-glow giving in networks with multiple public goods

This paper explores a voluntary contribution game in the presence of warm-glow effects. There are many public goods and each public good benefits a different group of players. The structure of the game induces a bipartite network structure, where players are listed on one side and the public good groups they form are listed on the other side. The main result of the paper shows the existence and uniqueness of a Nash equilibrium. The unique Nash equilibrium is also shown to be asymptotically stable. Then the paper provides some comparative statics analysis regarding pure redistribution, taxation and subsidies. It appears that small redistributions of wealth may sometimes be neutral, but generally, the effects of redistributive policies depend on how public good groups are related in the contribution network structure.     

A mathematical analysis for a model arising from public goods games

We study the effects of altruistic behaviors in a public goods game model which describes the competition between the farmers and the exploiters. Corresponding to different parametric regions, we analyze in detail the stability of the equilibrium states and obtain attraction regions for stable equilibria. Then using the upper–lower solution method and monotone iterations, we further show that for a family of wave speeds, there exist traveling wave solutions connecting one of the unstable states to the stable state. This answers a conjecture made by Wakano in [J.Y. Wakano, A mathematical analysis on public goods games in the continuous space, Math. Biosci. 201 (2006) 72–89]. The results indicate that when the penalty for the altruistic behavior is small, the growth rate of the population determines its survival or extinction states in the long run. Furthermore, if the two populations have the same total growth rate, altruism in the competition leads to a wide range of co-existent states. Numerical simulations are also presented to illustrate the theoretical results.     

Utilization of mathematical programming for public systems: An application to effective formation of integrated regional information networks

This paper concerns a methodological reflection on the multiobjective approach to public systems which involve group decision processes. Particular attention is given to an integrated program of regional systems which include value trade-offs between multiple objectives. Our intention is to combine the judgmental processes with the optimization processes in the soft public systems. A two-layer approach is applied. At the first layer, each regional program is formulated in mathematical programming based on a utility assessment with different regional characteristics. Each subsystem independently reflects its particular concern as a single agent. The dual optimal solutions obtained for each subsystem are treated as an index, or the theoretical prices, representing the value trade-offs among the multiple objectives. At the second layer, an effective formation of interregional cooperation for compromising the conflicting regional interests is examined. Ann-person cooperative game in the characteristic function form is used to evaluate the effectiveness of the cooperation. The characteristic function for the game is derived on the incremental value of the regional benefit after the formation of a cooperation. The nucleolus and the augmented nucleolus as the solution concepts of the cooperative game are used for indicating the effectiveness of the cooperation. Finally using alternative criteria, the results in assessing the best decisions are examined comparatively.     

The computation of a general equilibrium in a public goods economy

This paper presents an algorithm for computing approximations to a certain subset of Pareto optimal allocations in a public goods economy. Consumers are partitioned into a number of exogenous governmental jurisdictions, which provide public goods locally and raise revenue to cover their costs by means of a proportional wealth tax. The Pareto optimal allocations studied are consistent with profit maximization on the part of producers, and utility maximization over private goods bundles subject to after-tax budget constraints by consumers. The computational routine is based on the Scarf algorithm for computing fixed points.The origins of this research date back to the Dartmouth Workshop on Applications to economics of new methods of computing fixed points, held during the summer of 1972 under the direction of H. Scarf. The author wishes to thank the participants in this workshop for many stimulating discussions. Also the provision of computer time by the Computer Research Center of the National Bureau of Economic Research is gratefully acknowledged. FIXPOINT, an interactive computer system developed at the Computer Research Center, was used in performing the numerical computations presented in the paper.     

Endogenous effort in communication networks under strategic complementarity

This article examines individual incentives to produce information on communication networks. In our setting, efforts are strategic complements along communication paths with convex decay. We analyze the relationship between efforts and centrality on a set of networks which are unambiguous in terms of ordinal centrality. We first show that in both dominant and dominated equilibria central agents exert more effort. Second, we explore the issue of social coordination induced by our game.     

Heuristics for multi-period capacity expansion in local telecommunications networks

In this paper, different heuristics are devised to solve a multi-period capacity expansion problem for a local access telecommunications network with a tree topology. This expansion is done by installing concentrators at the nodes and cables on the links of the network. The goal is to find a least cost capacity expansion strategy over a number of periods to satisfy the demand. A local search heuristic is first proposed to improve previously reported results on problem instances based on different cost and demand structures. This heuristic is then integrated into a genetic algorithm to obtain further improvements.     

Stability analysis of data-driven local model networks

This article discusses stability analysis of data-driven dynamic local model networks. In contrast to traditional fuzzy modelling, the structure and complexity of such model architectures is not unique when only observed input- and output data are available for their parametrization. The present article complements the well-known trade-off between accuracy and complexity by the notion of stability. For this purpose, existing Lyapunov stability criteria for local model networks are extended by a decay rate which represents a scalar and quantitative stability measure. It allows to compare models with different degrees of complexity also in view of their stability. For some of the commonly available Lyapunov stability criteria, the individual local model transitions are crucial. Therefore, in this article, an approach is introduced to determine the actually occurring model transitions by means of the identification data. The methods presented in the article are illustrated and discussed by means of a simulation example. It is shown how model complexity and the related approximation quality can have an adverse impact on the stability and how the outcome of different Lyapunov criteria is affected by the proper determination of local model transitions.     

Models for planning capacity expansion in local access telecommunication networks

The rapid progress of communications technology has created new opportunities for modeling and optimizing the design of local telecommunication systems. The complexity, diversity, and continuous evolution of these networks pose several modeling challenges. In this paper, we present an overview of the local telephone network environment, and discuss possible modeling approaches. In particular, we (i) discuss the engineering characteristics of the network, and introduce terminology that is commonly used in the communications industry and literature; (ii) describe a general local access network planning model and framework, and motivate different possible modeling assumptions; (iii) summarize various existing planning models in the context of this framework; and (iv) describe some new modeling approaches. The discussion in this paper is directed both to researchers interested in modeling local telecommunications systems and to planners interested in using such models. Our goal is to present relevant aspects of the engineering environment for local access telecommunication networks, and to discuss the relationship between engineering issues and the formulation of economic decision models. We indicate how changes in the underlying switching and transmission technology affect the modeling of the local telephone network. We also review various planning issues and discuss possible optimization approaches for treating them.This research was initiated through a grant from GTE Laboratories, IncorporatedSupported in part by an AT&T research award.Supported in part by Grant No. ECS-8316224 from the Systems Theory and Operations Research Program of the National Science Foundation.     

An improved local branching approach for train formation planning

The train formation plan (TFP) determines routing and frequency of trains, and assigns the demands to trains. In this paper, an improved local branching algorithm is proposed for the TFP model in Iranian railway. This solution strategy is exact in nature, although it is designed to improve the heuristic behavior of the mixed integer programming (MIP) solver at hand. In the local branching algorithm, additional constraints are built in the model for the binary variables, but in the improved local branching algorithm, the additional constraints are built in the model for integer variables. A state-of-the-art method is applied for parameter tuning using design of experiments approach. To evaluate the proposed solution method, we have simulated and solved twenty test problems. The results show the efficiency and effectiveness of the proposed approach. The proposed algorithm is implemented for Iranian Railway network as a case study.     

Evaluation and optimization of urban public transportation networks

So far, not much attention has been given to the problem of improving public transportation networks. In many cities these networks have been built sequentially and do not fit to the needs of the users any more. The results are long travel times and an unnecessarily high number of people who have to transfer. Compared to other investments for improving the service level of public transportation systems, the costs of rerouting the public vehicles are low and can, yet, highly improve the performance of the system.To evaluate a public transportation network, the shortest distance and the shortest route from node x to node y, taking the waiting times for a vehicle into account, must be known.It is shown in this paper, how to compute distances and routes efficiently for large networks. Using this algorithm it is described how to evaluate the average transportation cost of the passengers in a public transportation network.In the second part of the paper a heuristic algorithm is stated that improves a public transportation network using the average transportation cost as the objective.Finally, some experiences with real world problems are reported.     

A collective model for the formation of public opinion: An application to nuclear public acceptance

A collective model is proposed for the formation of public opinion and applied to the problem of public acceptance for nuclear energy in Japan. The selection of attitude for the people to a certain subject is assumed to be made depending on the sociopsychological pressure suffering from the surroundings, and on the quality and quantity of information on that subject released from the newsmedia. The reportorial stance of the newsmedia, on the other hand, is assumed to vary depending on, not only public opinion, but also the resultant of the mutual watch of the newsmedia to each other, concerning the state of information on the subject. Both an individual person and an individual medium are regarded as an interactive but structureless particle, and the interactions between the particles of the people and of media are described by introducing respective potentials of the type of molecular dynamics. Applying this model to the issue of electricity generation by nuclear energy, it was found to well reproduce the observed movement of public opinion in Japan. It also became clear that this sort of physical model is quite useful for understanding the status of socially collective phenomena in which nonlinearity and self-organization are strongly concerned.     

Dynamic programming based heuristics for the topological design of local access networks

This paper deals with the terminal layout problem, which is a problem arising in data communication network design. The problem consists of finding the best way to link terminals to a computer site and, in graph-theoretical terms, it resorts to determining a minimal spanning tree with an additional constraint (CMST). We present a class of heuristics that combine dynamic programming with clustering and decomposition techniques. More specifically, the original problem is transformed, either by clustering or decomposition, in order to obtain smaller size problems that can be handled by a dynamic programming approach. Such heuristics were specifically aimed at improving solutions produced by the Esau-Williams algorithm, which is one of the most effective heuristics presented in the literature for the CMST. Actually, computational experience confirms that such improvements can be achieved by the new heuristic.This research was partially supported by JNICT (Junta Nacional de Investigação Científica e Tecnológica) under Research Contract No. 87383/MIC.     

Two local dissimilarity measures for weighted graphs with application to protein interaction networks

We extend the Czekanowski-Dice dissimilarity measure, classically used to cluster the vertices of unweighted graphs, to weighted ones. The first proposed formula corresponds to edges weighted by a probability of existence. The second one is adapted to edges weighted by intensity or strength. We show on simulated graphs that the class identification process is improved by computing weighted compared to unweighted edges. Finally, an application to a drosophila protein network illustrates the fact that using these new formulas improves the ’biological accuracy’ of partitioning.     

Citizen coproduction and efficient public good provision: Theory and evidence from local public libraries

In both public administration and economics, efficiency is brought forward as an important criterion for evaluating administrative actions. Clearly, its value as an assessment principle depends on our ability to adequately measure efficiency. This article argues that citizen’s coproduction in public services requires a careful reassessment of how we approach the measurement of productive efficiency in public service delivery. Theoretically, we illustrate that using observable outcomes (e.g., library circulation, school results, health outcomes, fires extinguished, and crimes solved) as output indicators is inappropriate and leads to biased estimates of public service providers’ productive efficiency. This bias arises because citizens co-determine final outputs, leaving them at least partly beyond the service providers’ control. Empirically, we find supportive evidence of both the existence and importance of such ‘demand-induced’ bias.     

Some simple optimization techniques for self-organized public key management in mobile ad hoc networks

We consider some graph theoretical problems arising from security requirements in some communication networks. Basically one has to associate to each node of a directed graph G=(V,E) a partial subgraph of G. A solution consists hence of a collection of |V| subgraphs, subject to some packing constraints or connectivity requirements. We first describe the usual graph theoretical model and we review a known construction procedure for which we point out some basic properties. We then study in more details the case of complete graphs and show the existence of a solution with a guaranteed quality. Next, we study the performance of the construction procedure and we propose an additional construction. We attempt to characterize the cases in which either construction is preferable. In the last section, a tabu search approach is proposed and tested on a sample of numerical examples.     

A fast local search method for minimum energy broadcast in wireless ad hoc networks

Local search methods are often used to reduce the power consumption of broadcast routing in wireless networks. For a classic method, sweep, the best available time complexity result is O(|V|⁴). We present an O(|V|²)-time method, which exhaustively removes unnecessary transmissions yielding a solution comparable to that of sweep.     

Modelling public transport trips by radial basis function neural networks

Artificial neural networks (ANNs) are one of the recently explored advanced technologies, which show promise in the area of transportation engineering. The presented study used two different ANN algorithms, feed forward back-propagation (FFBP) and radial basis function (RBF), for the purpose of daily trip flow forecasting. The ANN predictions were quite close to the observations as reflected in the selected performance criteria. The selected stochastic model performance was quite poor compared with ANN results. It was seen that the RBF neural network did not provide negative forecasts in contrast to FFBP applications. Besides, the local minima problem faced by some FFBP algorithms was not encountered in RBF networks.