José Eugenio Leal

A Model for the Strategic Planning of National Freight Transportation by Rail

Recently, we developed a multimode multiproduct network optimization model, that is the network assignment method implemented in an interactive-graphic system for the strategic analysis and planning of national freight transportation systems, called STAN. For STAN, we developed a modeling framework of the rail freight transportation system, its components, operations and goals, that is adapted for both the strategic objectives of the planning system and the representation of the other transportation modes that compose a national multimode transportation system. The objective of this paper is to present and analyze the rail component of this strategic model of a national freight transportation system. We show how the rail model is integrated into STAN, as well as how this modeling framework may be used to represent a number of realistic scenarios.

A spatial price equilibrium model in the oligopolistic market for oil derivatives: an application to the brazilian scenario

This paper presents a spatial price equilibrium model in an oligopoly market for refined oil products. Till 1997 the Brazilian oil market was characterized by the state monopoly of Petrobras, which up to 2001 remained the only firm authorized to import oil derivatives. With several agents operating in the primary oil supply market, the government stopped fixing the prices for Petrobras, which started to determine the prices based on competition with other players. In this new scenario some questions arise regarding the price levels at which refined products will be supplied in different regions across Brazil as well as the capacity of national refineries to compete with imported products. To answer those and other questions, a new oligopoly spatial equilibrium model is herein proposed, taking into account the special characteristics of production of refined oil products. An iterative Gauss-Seidel-like algorithm with sequential adjustments was developed and applied to Brazilian market data. The model, the algorithm and its application are described in this work. Such a model may be used both by regulatory authorities and by companies in the sector.

A multi-objective ant colony optimization method applied to switch engine scheduling in railroad yards

This paper proposes an ant colony optimization algorithm to assist railroad yard operational planning staff in their daily tasks. The proposed algorithm tries to minimize a multi-objective function that considers both fixed and variable transportation costs involved in moving railroad cars within the railroad yard area. This is accomplished by searching the best switch engine schedule for a given time horizon. As the algorithm was designed for real life application, the solution must be delivered in a predefined processing time and it must be in accordance with railroad yard operational policies. A railroad yard operations simulator was built to produce artificial instances in order to tune the parameters of the algorithm. The project is being developed together with industrial professionals from the Tubarao Railroad Terminal, which is the largest railroad yard in Latin America.

Uso do conceito de hipercaminhos no transporte de carga: uma análise exploratória

It is important for cargo shippers to have options to choose different paths and modes of transport at different times to reduce your total expected cost. The purpose of this paper is to present an approach that makes use of the hyperpaths concept to support the decision of the cargo shippers of choosing paths and transports modes. It is suggested a model for selecting optimal routes by mathematical programming for multimodal freight transportation which employs the concept of hyperpath. This model produces as result a strategic set of best paths for the shipper, according to the definition of hyperpath, derived from the scientific literature of models of public transport. Adjustments of this approach are presented for the transport of cargo. An illustrative example of the model is used to show its application.

ACO applied to switch engine scheduling in a railroad yard

This reasearch studies ACO algorithms for the switch engine scheduling in a Railroad Yard. The cars are moved individually or grouped into blocks by a set of locomotives called switch engines which are dedicated to moving around the cars in the yard. The need for moving comes from the fact that the arriving trains are disassembled into blocks of cars, undergo some operations like, loading, unloading and cleaning and finally are assembled into a new train. Each moving request is called a switch order. The decision of which switch engine will execute which switch order and the sequence of that executution is the core of our problem. The optimization of this schedule reduces the overall operational costs of the yard as weel as the time to assemble new trains, thus leading to a more productive railroad system.

Alocação de fluxos de passageiros em uma rede de transporte público de grande porte formulado como um problema de inequações variacionais

The biggest cities in the world faced problems in the transportation system. In order to plan the system, decision makers need tools, which enable them to make good approximate simulations of the routing choice process for all the users. The work presents the formulation and implementation of a passenger flow assignment model for a transit transportation network. The model has been stated as a variational inequality problem. The solution algorithm makes some assumptions about the process of flow partition between alternative line segments. The procedure has been implemented using Delphi language and applied in tests with small networks published in the literature. A bigger experiment has been conducted with the transit network of Rio de Janeiro city.

Discrete-event simulation software selection for manufacturing based on the maturity model

Abstract The main objective of this research is to develop a new method to help an industry select the right DESS (discrete-event simulation software), which helps improve the productivity of a given process. This paper addresses this issue by developing a methodology that undertakes two aspects of the problem. First, it proposes a methodology that allows for companies to self-assess their current internal processes based on a maturity model to identify where they stand in the maturity continuum for simulation. Second, it applies the analytical hierarchical process (AHP) to support simulation software selection by detailing and weighting the components that are important for the specific company to meet its business objectives. To the best of our knowledge, there are no other studies that combine these two methodological tools to help decision making for DESS selection.

COMPUTING MAX FLOWS THROUGH CUT NODES

In this work, the presence of cut nodes in a network is exploited to propose a competitive method for the multi-terminal maximum flow problem. The main idea of the method is based on the relation between cut-trees and cut nodes, which is observed in the context of sensitivity analysis on the variation of edges capacities. Computational experiments were conducted with the proposed algorithm, whose results were compared with the ones of Gusfield, for randomly generated and well-known instances of the literature. The numerical results demonstrate the potential of the method for some classes of instances. Moreover, the proposed method was adapted for the single maximum flow problem, but failed to improve existing running times for the very same classes of instances.