Demand/Supply Relationship in Transportation Network Design Problems: A Genetic Algorithm Approach

by Yihua Xiong, Florida Int Univ, Miami, United States,
Jerry B. Schneider, Florida Int Univ, Miami, United States,

Document Type: Proceeding Paper

Part of: Computing in Civil Engineering


The cumulative genetic algorithm (CGA) has its significant advantages over the heuristic algorithms in dealing with transportation network design problems. Using CGA, the entire solution space can be explored and the optimal solutions, which form a boundary of the solution space, can be identified. Thus, with each given demand matrix, an optimal `solution space boundary' can be obtained. Since the demand is changing, a series of demand matrices can be used and therefore several such solution space boundaries can be generated. By analyzing these boundaries, a clear relationship between future demand and supply will be illustrated. This relationship can be used to make the transportation network improvement plan.

Subject Headings: Algorithms | Domain boundary | Matrix (mathematics) | System analysis | Space exploration | Travel time | Transportation studies

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