Reference point based multi-objective optimization using evolutionary algorithms
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Proceedings of the 12th annual conference companion on Genetic and evolutionary computation
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
Metaheuristic approaches to tool selection optimisation
Proceedings of the 14th annual conference on Genetic and evolutionary computation
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This work presents a new multi-objective approach to tool sequence optimisation in end milling applications. In this way, the process planner is presented with a selection of solutions offering a good trade-off between total machining time and total tooling costs. The majority of previous research has concentrated either on optimising tool selection or machining parameters. In the presented approach, each tool in a sequence has its most important parameter, cutting speed, simultaneously optimised creating a problem with both discrete and continuous properties. The major constraint, excess material, is included as an additional objective. The problem is solved using NSGA-II with preferential search modifications to guide solutions towards the feasible region.