Abstract
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.
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