Metaheuristics: Progress as Real Problem Solvers pp 227-241 | Cite as
Bi-Objective Sequencing of Cutting Patterns
Abstract
Sequencing cutting pattems problems arise in several industries. Given a set of cutting patterns and a given objective, a sequencing problem consists of finding a permutation of patterns that optimises the objective. Single objective problems are NP-hard. Approaches available in the literature have only dealt with single objective problems, and consider heuristics and metaheuristics. Single objective optimisation approaches are myopic regarding other objectives and may loose Pareto optimal solutions. We propose a bi-objective sequencing problem considering the minimisation of the maximum number of open stacks and the minimisation of the average order spread. To approximate the Pareto optimal set we used multi-objective evolutionary algorithms. The bi-objective optimisation approach can provide knowledge about the solution space that would not have been achieved with a pure single objective approach.
Key words
Cutting-stock sequencing problems multi-objective evolutionary algorithmsPreview
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