Hybrid Search for Faster Production and Safer Process Conditions in Friction Stir Welding

Cem Celal Tutum (Invited author), Kalyanmoy Deb (Invited author), Jesper Henri Hattel (Invited author)

Research output: Contribution to journalConference articleResearchpeer-review


The objective of this paper is to investigate optimum process parameters and tool geometries in Friction Stir Welding (FSW) to minimize temperature difference between the leading edge of the tool probe and the work piece material in front of the tool shoulder, and simultaneously maximize traverse welding speed, which conflicts with the former objective. An evolutionary multi-objective optimization algorithm (i.e. NSGA-II), is applied to find multiple trade-off solutions followed by a gradient-based local search (i.e. SQP) to improve the convergence of the obtained Pareto-optimal front. In order to reduce the number of function evaluations in the local search procedure, the obtained non-dominated solutions are clustered in the objective space and consequently, a postoptimality study is manually performed to find out some common design principles among those solutions. Finally, two reasonable design choices have been offered based on several process specific performance and cost related criteria.
Original languageEnglish
Book seriesLecture Notes in Computer Science
Pages (from-to)603-612
Publication statusPublished - 2011
EventProceedings of Simulated Evolution and Learning - Indian Intitute of Technology Kanpur, India.
Duration: 1 Jan 2010 → …


ConferenceProceedings of Simulated Evolution and Learning
CityIndian Intitute of Technology Kanpur, India.
Period01/01/2010 → …


  • Friction stir welding
  • Material flow
  • Evolutionary multi-objective optimization
  • ε-constraint method
  • Thermal simulation
  • Hybrid search
  • Gradient-based local search technique

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