A Hybrid Multi-objective Evolutionary Approach to Engineering Shape Design
EMO '01 Proceedings of the First International Conference on Evolutionary Multi-Criterion Optimization
Modeling and simulation of cataract surgery processes
Winter Simulation Conference
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
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This research is motivated by a scheduling problem found in a German eye hospital. We propose heuristics to schedule the daily surgeries. Our objective is to reduce the waiting time of the patients and to increase the utilization of the operating rooms (ORs). A Non-Dominated Sorting Genetic Algorithm II (NSGA-II) scheme with a random key representation is proposed to tackle this problem. The NSGA-II approach is hybridized with a local search procedure. Because of the stochastic surgery durations, discrete-event simulation is used to assess the fitness of the chromosomes. The schedules are executed using a simulation model of the eye hospital. Different rescheduling strategies are researched.