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A Tabu Search-Based Optimization Approach for Process Planning

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Part of the Lecture Notes in Computer Science book series (LNAI,volume 2774)

Abstract

In this paper, crucial processes in a computer-aided process planning system, such as selecting machining resources, determining set-up plans and sequencing operations of a part, have been considered simultaneously and modelled as a constraint-based optimization problem, and a Tabu search-based approach has been proposed to solve it effectively. In the optimization model, costs of the utilized machines and cutting tools, machine changes, tool changes, set-ups and departure of good manufacturing practices (penalty function) are integrated as an optimization evaluation criterion. A case study, which is used to compare this approach with the genetic algorithm and simulated annealing approaches, is discussed to highlight the advantages of this approach in terms of solution quality, computation efficiency and the robustness of the algorithm.

Keywords

  • Tabu Search
  • Tabu List
  • Current Plan
  • Tool Change
  • Simulated Annealing Approach

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

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© 2003 Springer-Verlag Berlin Heidelberg

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Li, W.D., Ong, S.K., Lu, Y.Q., Nee, A.Y.C. (2003). A Tabu Search-Based Optimization Approach for Process Planning. In: Palade, V., Howlett, R.J., Jain, L. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2003. Lecture Notes in Computer Science(), vol 2774. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45226-3_137

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  • DOI: https://doi.org/10.1007/978-3-540-45226-3_137

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40804-8

  • Online ISBN: 978-3-540-45226-3

  • eBook Packages: Springer Book Archive