A study of permutation crossover operators on the traveling salesman problem
Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
Proceedings of the First International Conference on Evolutionary Multi-Criterion Optimization
EMO '01 Proceedings of the First International Conference on Evolutionary Multi-Criterion Optimization
Proceedings of the 2nd international conference on Evolutionary multi-criterion optimization
EMO'03 Proceedings of the 2nd international conference on Evolutionary multi-criterion optimization
A hybrid genetic algorithm for the capacitated vehicle routing problem
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
EMO'07 Proceedings of the 4th international conference on Evolutionary multi-criterion optimization
On the interactive resolution of multi-objective vehicle routing problems
EMO'07 Proceedings of the 4th international conference on Evolutionary multi-criterion optimization
An improved multi-objective evolutionary algorithm for the vehicle routing problem with time windows
Computers and Operations Research
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In this paper, we focus on the importance of examining characteristics of non-dominated solutions especially when a user should select only one solution from non-dominated solutions at a time, and select another solution due to the change of problem conditions. Although he can select any solution from non-dominated solutions, the similarity of selected solutions should be considered in practical cases. We show simulation results on vehicle routing problems that have two demands of customers: Normal Demand Problem (NDP) and High Demand Problem (HDP). In our definition the HDP is an extended problem of NDP. We examined two ways of applying an EMO algorithm. One is to apply it to each problem independently. The other is to apply it to the HDP with initial solutions generated from non-dominated solutions for the NDP. We show that the similarity of the obtained sets of non-dominated solutions is enhanced by the latter approach.