A Genetic Symbiotic Algorithm Applied to the Cutting Stock Problem with Multiple Objectives
نویسندگان
چکیده
This work presents a genetic symbiotic algorithm to solve the one-dimensional cutting stock problem with multiple objectives. We considered two important objectives for an industry (1) cost of trim loss and (2) cost of setup. We use a symbiotic relationship, between the population of solutions and the population of cutting patterns, together with a niche strategy to obtain an approximation of the Pareto-front. The evolutionary approach promotes a significant diversity in the population, which is a desirable condition to solve a multi-objective combinatorial optimization problem. Results of the computational experiments with instances from a chemical-fiber company and with random instances are reported.
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A Genetic Symbiotic Algorithm Applied to the One-dimensional Cutting Stock Problem
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