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Genetic Algorithm-Based Approach for Transportation Optimization Problems

By: William H. K. Lam
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The motivation for using genetic algorithms (GAs) for transportation optimization problems is due to the globality, parallelism and robustness of GAs. In addition, GAs are simple and powerful in their search for improvement, and not fundamentally limited by restrictive assumption about the search space. Recent related studies using GAs have shown advantages in dealing with non-convexity, locality and complexity of transportation optimization problems, especially in optimal pavement management (Fwa et al., 1994), optimal traffic signal control (Hadi and Wallace, 1993; Memon and Bullen, 1996; Lo et al., 2000), urban transit system design problems (Pattnaik et al., 1998; Chakrobort et al., 1998), aircraft gate re-assignment problem (Gu and Chung...

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