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Information Journal Paper

Title

A GENETIC ALGORITHM APPROACH FOR STATISTICAL MULTI-RESPONSE MODELS OPTIMIZATION: A CASE STUDY

Pages

  131-137

Abstract

 One of the most important and cost consuming factors which has great effect on the die-cut cartons manufacturing system is its mold. Here we propose a GENETIC ALGORITHM to optimize this products quality level. Using the DESIGN OF EXPERIMENTS, we define the effective elements of problem. Then we model it by central composed design (one of the most common designs in RESPONSE SURFACE METHODOLOGY) and apply GENETIC ALGORITHM to optimize the obtained model. A comparison is carried out on the proposed gentic algorithm and two other heuristic methods. Finally to determine the best solution, TOPSIS METHOD is implemented to sort solutions of algorithms.

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    APA: Copy

    AMIRI, MAGHSOUD, FALAH JAMSHIDI, S., & SALEHI SEDGHIANI, J.. (2009). A GENETIC ALGORITHM APPROACH FOR STATISTICAL MULTI-RESPONSE MODELS OPTIMIZATION: A CASE STUDY. INDUSTRIAL ENGINEERING & MANAGEMENT SHARIF (SHARIF: ENGINEERING), 25(49), 131-137. SID. https://sid.ir/paper/107576/en

    Vancouver: Copy

    AMIRI MAGHSOUD, FALAH JAMSHIDI S., SALEHI SEDGHIANI J.. A GENETIC ALGORITHM APPROACH FOR STATISTICAL MULTI-RESPONSE MODELS OPTIMIZATION: A CASE STUDY. INDUSTRIAL ENGINEERING & MANAGEMENT SHARIF (SHARIF: ENGINEERING)[Internet]. 2009;25(49):131-137. Available from: https://sid.ir/paper/107576/en

    IEEE: Copy

    MAGHSOUD AMIRI, S. FALAH JAMSHIDI, and J. SALEHI SEDGHIANI, “A GENETIC ALGORITHM APPROACH FOR STATISTICAL MULTI-RESPONSE MODELS OPTIMIZATION: A CASE STUDY,” INDUSTRIAL ENGINEERING & MANAGEMENT SHARIF (SHARIF: ENGINEERING), vol. 25, no. 49, pp. 131–137, 2009, [Online]. Available: https://sid.ir/paper/107576/en

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