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Through an extended numerical example, this paper develops a diagrammatic analysis of steady-state parking and traffic congestion in an isotropic downtown. The model incorporates curbside parking, garage parking, and price-sensitive travel demand in a unified setting, and provides systematic policy analysis. In particular, we examine the deadweight loss associated with underpriced curbside parking, as well as first- and second-best curbside parking capacities. We also explore the transient dynamics and stability of various downtown traffic equilibria.

This paper investigates the economics of curbside parking time limits. It argues that curbside parking time limits provide a way to subsidize short-term parking without generating cruising for parking. The paper develops the argument in the context of the integrated model of downtown parking and traffic congestion presented in Arnott and Rowse (2009), extended to incorporate heterogeneity in value of time and parking duration.

This paper investigates first-best downtown transportation systems in the medium run for a broad range of demand densities. A downtown transportation system is assumed to include a subway system that operates on its own network and a congestible street system that accommodates both buses and cars. A “subway” is any mass transit mode that operates on an exclusive right of way; a “bus” is any mass transit mode for which there congestion interaction with cars1. The analysis is “medium run” in the sense that the subway and road networks are fixed, as are their link capacities, and “first-best” in the sense that the planner faces only technological constraints. The analysis is “downtown” only in the sense that it focuses on high levels of demand density that for most metropolitan areas occur only downtown. The analysis is static (stationary state), ignoring the intra-day dynamics of travel and congestion.

This paper investigates the economics of curbside parking time limits. It argues that curbside parking time limits provide a way to subsidize short-term parking without generating cruising for parking. The paper develops the argument in the context of the integrated model of downtown parking and traffic congestion presented in Arnott and Rowse (2009), extended to incorporate heterogeneity in value of time and parking duration.

Water runoff valuing proved to be not highly significant in optimal forest management. Utilization of a linear programming model that optimizes net present value of timber production and water runoff revealed that inclusion of a moderate or high value for water runoff does not result to modification of optimal harvest pattern. Such action also does not cover smaller blocks' additional costs.

A dynamic computational model has been used to analyze the economic and social aspects of natural gas royalty taxation. Through a sensitivity analysis of natural gas allocation for the Canadian province of British Colombia, it has been determined that moderate royalty taxes above 30% pose small proportionate social welfare losses and generate only less than 6.5% of the fixed royalty. Moreover, multi-depletion paths have been determined to be optimal for nonrenewable resources and taxation.

Research was conducted on the efficient allocation of a nonconventional and nonrenewable source. Tight gas was chosen as the resource, and declining marginal costs for nonconventional resources were integrated into a model of Canadian natural gas allocation. The result is a representation of rising, declining and constant marginal costs for various gas resources and data hint at multiple price equilibria as well as the existence of likelihood extreme optimal solutions.

Stanford University's ninth Energy Modeling Forum study analyzes models for studying the natural gas trade between the US and Canada. The GRI-North America model seems the most likely to be adopted as the standard due to availability, appeal and validity. However, model users are warned that all models make extensive use of assumptions and uncertain parameters such as legislation, world markets, tariff and environmental actions may have greater effects on results than can be handled or interpreted by the models.

Recent advances in mathematical programming methods and computing technology have the potential for overcoming the many formidable barriers to the widespread solution of nonlinear spatial models. In particular, the recent public availability of the software package MINOS/AUGMENTED has major implications for both policy and theoretical research involving spatial models. In this paper, mathematical programming formulations of two highly nonlinear spatial models are provided, model solutions presented, and associated computational experience discussed. In addition, related work is discussed briefly and suggestions are advanced concerning the potential role of the package in furthering the objectives of this related work. [ABSTRACT FROM AUTHOR]

Large-scale mixed-integer linear programming (MILP) models may easily prove extraordinarily difficult to solve, even with efficient commercially implemented MILP solution codes. Drawing on experience gained in solving and analyzing three intertemporal investment planning MILP models for electric power supply, this note offers several practical suggestions for reducing computer solution times for general production-allocation MILP models. Solution time reduction stems from judicious use of the powerful computational capabilities of existing commercial linear programming codes in conjunction with information known or to be learned by the practitioner about the model's structure. [ABSTRACT FROM AUTHOR]

Evaluates the economic benefits of cooperative power supply expansion by two or more electric utilities in Canada. Implications of the rising cost of electrical energy; Impact the of reduction of cost in transmission; Reliability in supply.