On the effectiveness of connection tolls in fair cost facility location games

We investigate the effectiveness of tolls to reduce the inefficiency of Nash equilibria in the classical fair cost facility location game. In this game, every terminal corresponds to a selfish player who wants to connect to some facility at minimum cost. The cost of a player is determined by the connection cost to the chosen facility plus an equal share of its opening cost. We are interested in the problem of imposing tolls on the connections to induce a socially optimal Nash equilibrium such that the total amount of tolls is minimized. It turns out that this problem is challenging to solve even for simple special cases. We provide polynomial-time algorithms for (i) instances with two facilities, and (ii) instances with a constant number of facilities arranged as a star. Our algorithm for (ii) exploits a relation between our tolling problem and a novel bipartite matching problem without crossings, which we prove to be NP-hard

Jogos de localização de instalações não cooperativos e percepção de custos

Orientadores: Eduardo Candido Xavier, Guido SchäferTese (doutorado) - Universidade Estadual de Campinas, Instituto de ComputaçãoResumo: Esta tese de doutorado cobre a interseção entre problemas de localização de instalações e teoria dos jogos algorítmica não cooperativa, com ênfase em alterações da percepção de custos de cada jogador e seu efeito na qualidade de equilíbrios. O problema de localização de instalações é um dos problemas fundamentais em otimização combinatória. Em sua versão clássica, existe um conjunto de terminais e um conjunto de instalações, e cada terminal necessita ser conectado a uma instalação, para que esta providencie bens ou serviços. O objetivo é minimizar o total dos custos associados à abertura das instalações e à conexão dos terminais a essas instalações. Na prática, existem diversos cenários onde é inviável ou não é desejável que uma autoridade central única decida como clientes devem escolher as instalações às quais se conectam. Dessa forma, é importante estudar como a independência desses terminais pode afetar a eficiência social e a complexidade computacional para esses cenários. A teoria dos jogos algorítmica pode ser útil para tais cenários, em particular sua parte não cooperativa. A teoria dos jogos algorítmica preenche uma lacuna entre a ciência da computação teórica e a teoria dos jogos, e está interessada em questões como a complexidade computacional de se encontrar equilíbrios, o quanto o bem-estar social pode ser perdido devido ao egoísmo de jogadores e como desenvolver mecanismos para garantir que o melhor interesse dos jogadores se alinhe com o ótimo social. Nesta tese, estudamos jogos de localização de instalações não cooperativos e algumas de suas variantes. Focamos em responder questões relativas à existência de equilíbrios de Nash puros e sobre as principais medidas de perda de eficiência, o preço da anarquia e preço da estabilidade. Apresentamos uma revisão das descobertas mais importantes para as variantes básicas, com novos resultados nos casos onde nenhum era conhecido. Para a versão capacitada desses jogos, mostramos que, enquanto a simultaneidade pode levar a uma perda de eficiência ilimitada, quando se admite a sequencialidade de jogadores, é possível mostrar que a perda de eficiência tem limites. Também investigamos como mudanças na percepção de custo podem afetar a qualidade de equilíbrios de duas maneiras: através de jogadores altruístas e de esquemas de taxação. No primeiro, adaptamos resultados de jogos de compartilhamento justo de custos e apresentamos novos resultados sobre uma versão sem regras de compartilhamento. No último, propomos um modelo de mudança na percepção de custos, onde os jogadores consideram um pedágio adicional em suas conexões ao calcular seus custos. Apresentamos limitantes para o custo total das taxas no problema de pedágios mínimos, onde o objetivo é encontrar o valor mínimo de pedágio necessário para garantir que um determinado perfil de estratégia socialmente ótimo seja escolhido pelos jogadores. Mostramos algoritmos para encontrar pedágios ótimos para tal problema em casos especiais e relacionamos esse problema a um problema de emparelhamento NP-difícilAbstract: This Ph.D. thesis covers the intersection between facility location problems and non-cooperative algorithmic game theory, with emphasis on possible changes in cost perception and its effects in regards to quality of equilibria. The facility location problem is one of the fundamental problems in the combinatorial optimization field of study. In its classic version, there exists a set of terminals and a set of facilities, and each terminal must be connected to a facility, in order for goods or services to be provided. The objective is to minimize the total costs associated with opening the facilities and connecting all the terminals to these facilities. In practice, there are multiple scenarios where it is either infeasible or not desirable for a single central authority to decide which facilities terminals connect to. Thus, it is important to study how the independence of these terminals may affect social efficiency and computational complexity in these scenarios. For this analysis algorithmic game theory can be of use, in particular its non-cooperative part. Algorithmic game theory bridges a gap between theoretical computer science and game theory, and is interested in questions such as how hard it is computationally to find equilibria, how much social welfare can be lost due to player selfishness and how to develop mechanisms to ensure that players' best interest align with the social optimum. In this thesis we study non-cooperative facility location games and several of its variants. We focus on answering the questions concerning the existence of pure Nash equilibria and the main measures of efficiency loss, the price of anarchy and the price of stability. We present a review of the most important findings for the basic variants and show new results where none were known. For the capacitated version of these games, we show that while simultaneity may lead to unbounded loss of efficiency, when sequentiality is allowed, it is possible to bound the efficiency loss. We also investigate how changes in players' perception of cost can affect the efficiency loss of these games in two ways: through altruistic players and through tolling schemes. In the former we adapt results from fair cost sharing games and present new results concerning a version with no cost sharing rules. In the latter, we propose a model for change in cost perception where players consider an additional toll in their connections when calculating their best responses. We present bounds for total toll cost in the minimum toll problem, where the objective is to find the minimum amount of tolls needed to ensure that a certain socially optimal strategy profile will be chosen by players. We show algorithms for finding optimal tolls for the minimum toll problem in special cases and provide some insight into this problem by connecting it to a matching problem which we prove is NP-hardDoutoradoCiência da ComputaçãoDoutor em Ciência da Computação147141/2016-8CAPESCNP

Privatization and the Public Interest: The Need for Transparency and Accountability in Chicago's Public Asset Lease Deals

Examines the appeal and risks of infrastructure privatization and Chicago's history with privatization deals. Recommends public interest principles for future deals, rules and processes for vetting proposals, and a commitment to government transparency

Collaborative Funding to Facilitate Airport Ground Access, Research Report 11-27

This report presents the findings and conclusions from a research study that has examined the challenges of funding airport ground access projects and the role of collaborative funding strategies between the different agencies that typically become involved in such projects. The report reviews the recent literature on funding airport ground access projects, as well as funding transportation projects more generally. This is followed by a detailed review of current federal transportation funding programs relevant to airport ground access projects, as well as a discussion of state and local funding programs and potential opportunities for private-sector funding. A major component of the research described in the report consists of detailed case studies of seven selected airport ground access projects, including a major intermodal center, two automated people-mover projects, two airport access highway projects, and two airport rail links. These case studies examine the history of each project, the costs involved, and the funding programs and mechanisms used to finance the projects. Based on the literature review, the review of current funding programs, and the case study findings, the report identifies potential funding strategies for intermodal airport ground access projects, requirements for effective implementation of these strategies, and a recommended approach to facilitate successful project development and implementation. The report also presents recommended changes to transportation funding program rules and regulations that could facilitate and simplify development of intermodal solutions to future airport ground access needs

Agent-Based Models of Highway Investment Processes: Forecasting Future Networks under Public and Private Ownership Regimes

The present highway funding system, especially fuel taxes, may become a less reliable revenue source in the future, while the transportation public agencies do not have sufficient financial resources needed to meet the increasing traffic demand. In the last two decades there has been increasing interest in utilizing private sector to develop, finance and operate new and existing roadways in the United States. While transportation privatization projects have shown signs of success, it is not always clear how to measure the true benefits associated with these projects for all stakeholders, including the public sector, the private sector and the public. "Win-win" privatization agreements are tricky to make due to conflicting nature of the various stakeholders involved. Therefore, there is a huge need to study the welfare impacts of various road privatization arrangements for the society as a whole, and the financial implications for private investors and public road authorities. In order to address these needs, first, an empirical analysis is performed to study the investment decision processes of public transportation agencies. Second, the agent-based decision-making model is developed to consider transportation investment processes at different levels of government which forecasts future transportation networks and their performance under both existing and alternative transportation planning processes. Third, various highway privatization schemes currently practiced in the U.S. are identified and an agent-based model for analyzing regulatory policies on private-sector transportation investments is developed. Fourth, the above mentioned models are demonstrated on the networks with grid and beltway topologies to study the impacts of topology configuration on the privatization arrangements. Based on the simulation results of developed models, a number of insights are provided about impacts of ownership structures on the socio-economic performance in transportation systems and transportation network changes over time. The proposed models and the approach can be used in long-run prediction of economic performance intended for describing a general methodology for transportation planning on large networks. Therefore, this research is expected to contribute significantly to the understanding and selecting proper road privatization programs on public networks

A Comparative Evaluation Of Fdsa,ga, And Sa Non-linear Programming Algorithms And Development Of System-optimal Methodology For Dynamic Pricing On I-95 Express

As urban population across the globe increases, the demand for adequate transportation grows. Several strategies have been suggested as a solution to the congestion which results from this high demand outpacing the existing supply of transportation facilities. High –Occupancy Toll (HOT) lanes have become increasingly more popular as a feature on today’s highway system. The I-95 Express HOT lane in Miami Florida, which is currently being expanded from a single Phase (Phase I) into two Phases, is one such HOT facility. With the growing abundance of such facilities comes the need for indepth study of demand patterns and development of an appropriate pricing scheme which reduces congestion. This research develops a method for dynamic pricing on the I-95 HOT facility such as to minimize total travel time and reduce congestion. We apply non-linear programming (NLP) techniques and the finite difference stochastic approximation (FDSA), genetic algorithm (GA) and simulated annealing (SA) stochastic algorithms to formulate and solve the problem within a cell transmission framework. The solution produced is the optimal flow and optimal toll required to minimize total travel time and thus is the system-optimal solution. We perform a comparative evaluation of FDSA, GA and SA non-linear programming algorithms used to solve the NLP and the ANOVA results show that there are differences in the performance of the NLP algorithms in solving this problem and reducing travel time. We then conclude by demonstrating that econometric iv forecasting methods utilizing vector autoregressive (VAR) techniques can be applied to successfully forecast demand for Phase 2 of the 95 Express which is planned for 201