Guideway Network Design of Personal Rapid Transit System: A Multiobjective Genetic Algorithm Approach

This paper ments a multiobjective genetic algorithm (MOGA) to find the optimal guideway networks (GNs) of personal rapid transit (PRT). The objective of the GN design problem (GNDP) is to find the GNs that minimize the construction cost and peak-hour traffic while satisfying the connectivity constraint. To solve the GNDP, we develop an MOGA by modifying an impmved nondominated sorting genetic algorithm (NSGA-11). The developed MOGA inherits the advantages of NSGA-I1 and adopts a GNDP-specific mutation operator, which provides better solution quality. To verify the effectiveness and efficiency of the developed MOGA, we conducted numerical experiments on the GNDPs with up to 15 stations and 210 links.