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A Multi-Objective Evolutionary Algorithm for Solving Traveling Salesman Problems: Application to the Design of Polymer Extruders

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Adaptive and Natural Computing Algorithms

Abstract

A Multi-Objective Evolutionary Algorithm (MOEA) for solving Traveling Salesman Problems (TSP) was developed and used in the design of screws for twin screw polymer extrusion. Besides the fact that MOEA for TSP have already been developed, this paper constitutes an important and original contribution, since in this case, they are applied in the design of machines. The Twin- Screw Configuration Problem (TSCP) can be formulated as a TSP. A different MOEA is developed, in order to take into account the discrete nature of the TSCP. The algorithm proposed was applied to some case studies where the practical usefulness of this approach was demonstrated. Finally, the computational results are confronted with experimental data showing the validity of the approach proposed.

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Gaspar-Cunha, A. (2005). A Multi-Objective Evolutionary Algorithm for Solving Traveling Salesman Problems: Application to the Design of Polymer Extruders. In: Ribeiro, B., Albrecht, R.F., Dobnikar, A., Pearson, D.W., Steele, N.C. (eds) Adaptive and Natural Computing Algorithms. Springer, Vienna. https://doi.org/10.1007/3-211-27389-1_45

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  • DOI: https://doi.org/10.1007/3-211-27389-1_45

  • Publisher Name: Springer, Vienna

  • Print ISBN: 978-3-211-24934-5

  • Online ISBN: 978-3-211-27389-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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