Home About us Contact
|
Home About us Contact | ||
|
|
||
Network Design Problem (network + design_problem)
Selected AbstractsA Linear Model for the Continuous Network Design ProblemCOMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING, Issue 5 2006S. Travis Waller A linear programming formulation is introduced based on a dynamic traffic assignment (DTA) model that propagates traffic according to the cell transmission model. The introduced approach is limited to continuous link improvements and does not provide for new link additions. The main contribution of the article is to provide an analytical formulation for network design that accounts for DTA conditions that can be used for further analysis and extensions. The model is tested on a single destination example network, resembling a freeway corridor, for various congestion levels, loading patterns and budget sizes, to demonstrate the simplicity and effectiveness of the approach. [source] On the impact of the solution representation for the Internet Protocol Network Design Problem with max-hop constraintsNETWORKS: AN INTERNATIONAL JOURNAL, Issue 2 2004L. De Giovanni Abstract The IP (Internet Protocol) Network Design Problem can be shortly stated as follows. Given a set of nodes and a set of traffic demands, we want to determine the minimum cost capacity installation such that all the traffic is routed. Capacity is provided by means of links of a given capacity and traffic must be loaded on the network according to the OSPF-ECM (Open Shortest Path First,Equal Commodity Multiflow) protocol, with additional constraints on the maximum number of hops. The problem is strongly NP-Hard, and the literature proposes local search-based heuristics that do not take into account max-hop constraints, or assume a simplified OSPF routing. The core in a local search approach is the network loading algorithm for the evaluation of the neighbor solutions costs. It presents critical aspects concerning both computational efficiency and memory requirements. Starting from a tabu search prototype, we show how these aspects deeply impact on the design of a local search procedure, even at the logical level. We present several properties of the related network loading problem, that allow to overcome the critical issues and lead to an efficient solution evaluation. © 2004 Wiley Periodicals, Inc. NETWORKS, VoL. 44(2), 73,83 2004 [source] Tabu Search Strategies for the Public Transportation Network Optimizations with Variable Transit DemandCOMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING, Issue 7 2008Wei Fan A multi-objective nonlinear mixed integer model is formulated. Solution methodologies are proposed, which consist of three main components: an initial candidate route set generation procedure (ICRSGP) that generates all feasible routes incorporating practical bus transit industry guidelines; a network analysis procedure (NAP) that decides transit demand matrix, assigns transit trips, determines service frequencies, and computes performance measures; and a Tabu search method (TSM) that combines these two parts, guides the candidate solution generation process, and selects an optimal set of routes from the huge solution space. Comprehensive tests are conducted and sensitivity analyses are performed. Characteristics analyses are undertaken and solution qualities from different algorithms are compared. Numerical results clearly indicate that the preferred TSM outperforms the genetic algorithm used as a benchmark for the optimal bus transit route network design problem without zone demand aggregation. [source] Robust Transportation Network Design Under Demand UncertaintyCOMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING, Issue 1 2007Satish V. Ukkusuri The origin,destination trip matrices are taken as random variables with known probability distributions. Instead of finding optimal network design solutions for a given future scenario, we are concerned with solutions that are in some sense "good" for a variety of demand realizations. We introduce a definition of robustness accounting for the planner's required degree of robustness. We propose a formulation of the robust network design problem (RNDP) and develop a methodology based on genetic algorithm (GA) to solve the RNDP. The proposed model generates globally near-optimal network design solutions, f, based on the planner's input for robustness. The study makes two important contributions to the network design literature. First, robust network design solutions are significantly different from the deterministic NDPs and not accounting for them could potentially underestimate the network-wide impacts. Second, systematic evaluation of the performance of the model and solution algorithm is conducted on different test networks and budget levels to explore the efficacy of this approach. The results highlight the importance of accounting for robustness in transportation planning and the proposed approach is capable of producing high-quality solutions. [source] Genetic Algorithms for Optimal Urban Transit Network DesignCOMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING, Issue 3 2003Partha Chakroborty This article attempts to highlight the effectiveness of genetic algorithm (GA),based procedures in solving the urban transit network design problem (UTNDP). The article analyzes why traditional methods have problems in solving the UTNDP. The article also suggests procedures to alleviate these problems using GA,based optimization technique. The thrust of the article is three,fold: (1) to show the effectiveness of GAs in solving the UTNDP, (2) to identify features of the UTNDP that make it a difficult problem for traditional techniques, and (3) to suggest directions, through the presentation of GA,based methodologies for the UTNDP, for the development of GA,based procedures for solving other optimization problems having features similar to the UTNDP. [source] A reliability-based network design problemJOURNAL OF ADVANCED TRANSPORTATION, Issue 3 2005Piya Chootinan Abstract This paper presents a reliability-based network design problem. A network reliability concept is embedded into the continuous network design problem in which travelers' route choice behavior follows the stochastic user equilibrium assumption. A new capacity-reliability index is introduced to measure the probability that all of the network links are operated below their capacities when serving different traffic patterns deviating from the average condition. The reliability-based network design problem is formulated as a bi-level program in which the lower level sub-program is the probit-based stochastic user equilibrium problem and the upper level sub-program is the maximization of the new capacity reliability index. The lower level sub-program is solved by a variant of the method of successive averages using the exponential average to represent the learning process of network users on a daily basis that results in the daily variation of traffic-flow pattern, and Monte Carlo stochastic loading. The upper level sub-program is tackled by means of genetic algorithms. A numerical example is used to demonstrate the concept of the proposed framework. [source] Sensitivity analysis on stochastic equilibrium transportation networks using genetic algorithmJOURNAL OF ADVANCED TRANSPORTATION, Issue 3 2004Halim Ceylan Abstract This study deals with the sensitivity analysis of an equilibrium transportation networks using genetic algorithm approach and uses the bi-level iterative sensitivity algorithm. Therefore, integrated Genetic Algorithm-TRANSYT and Path Flow Estimator (GATPFE) is developed for signalized road networks for various level of perceived travel time in order to test the sensitivity of perceived travel time error in an urban stochastic road networks. Level of information provided to drivers correspondingly affects the signal timing parameters and hence the Stochastic User Equilibrium (SUE) link flows. When the information on road system is increased, the road users try to avoid conflicting links. Therefore, the stochastic equilibrium assignment concept tends to be user equilibrium. The GATPFE is used to solve the bi-level problem, where the Area Traffic Control (ATC) is the upper-level and the SUE assignment is the lower-level. The GATPFE is tested for six-junction network taken from literature. The results show that the integrated GATPFE can be applied to carry out sensitivity analysis at the equilibrium network design problems for various level of information and it simultaneously optimize the signal timings (i.e. network common cycle time, signal stage and offsets between junctions). [source] Bicriteria product design optimization: An efficient solution procedure using AND/OR treesNAVAL RESEARCH LOGISTICS: AN INTERNATIONAL JOURNAL, Issue 6 2002S. Raghavan Competitive imperatives are causing manufacturing firms to consider multiple criteria when designing products. However, current methods to deal with multiple criteria in product design are ad hoc in nature. In this paper we present a systematic procedure to efficiently solve bicriteria product design optimization problems. We first present a modeling framework, the AND/OR tree, which permits a simplified representation of product design optimization problems. We then show how product design optimization problems on AND/OR trees can be framed as network design problems on a special graph,a directed series-parallel graph. We develop an enumerative solution algorithm for the bicriteria problem that requires as a subroutine the solution of the parametric shortest path problem. Although this parametric problem is hard on general graphs, we show that it is polynomially solvable on the series-parallel graph. As a result we develop an efficient solution algorithm for the product design optimization problem that does not require the use of complex and expensive linear/integer programming solvers. As a byproduct of the solution algorithm, sensitivity analysis for product design optimization is also efficiently performed under this framework. © 2002 Wiley Periodicals, Inc. Naval Research Logistics 49: 574,592, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/nav.10031 [source] | |||||||||||||