2005 · 24 citations · 14 references
BusinessIndustrial EngineeringOperations ManagementOptimizationSchedulingTransportationEvolutionary ComputationMulti-objective OptimizationMulti-objective SchedulingMultiobjective OptimizationPareto OptimalityTransportation ProblemsEvolutionary AlgorithmsHeuristic AlgorithmsMass TransitMulti-objective Evolutionary ComputationMulti-objective Evolutionary OptimizationMultiobjective Evolutionary AlgorithmsTransit SchedulingTransportation Scheduling
This paper deals with the application of a heuristic-based evolutionary algorithms (EAs) on a specific industrial problem - the scheduling of rapid transit systems. The system under consideration is a medium-sized mass rapid transit (MRT) system and the dual objectives of minimizing operating costs and passenger dissatisfaction are considered. Making use of concepts such as Pareto-optimality and multiobjective evolutionary algorithms, the authors applied a multiobjective evolutionary algorithm (MOEA) to solve the problem. Comparison studies were done with current method, obtaining satisfactory results.
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