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Article type: Research Article
Authors: Fazlollahtabar, Hamed | Mahdavi-Amiri, Nezam | Muhammadzadeh, Amir
Affiliations: Faculty of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran | Faculty of Mathematical Sciences, Sharif University of Technology, Tehran, Iran | Department of Computer Science, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
Note: [] Corresponding author. Hamed Fazlollahtabar, Faculty of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran. Tel.: +989111137298; Fax: +981132190118; E-mail: [email protected]
Abstract: We concern with both time and cost optimization in an automated manufacturing system. In our proposed system, material handling is carried out by automated guided vehicles and robots for the manufacturing functions. In this way, defect rates, breakdown times, waiting time, processing time, and certain other parameters are not expected to be deterministic. Therefore, we apply stochastic programming to optimize the production time and material handling cost. The proposed stochastic program is a nonlinear model, for this reason we apply a successive linear programming (SLP) technique for its optimization. Numerical test results point to the inefficacy of the proposed optimization method for large sized problems. Hence, a genetic algorithm (GA) is presented to optimize large sized problems.
Keywords: Automated manufacturing system, stochastic programming, nonlinear optimization, genetic algorithm
DOI: 10.3233/IFS-141431
Journal: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 3, pp. 1461-1475, 2015
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