Using Multi-objective Ant Colony Optimization Algorithm to Solve a Multi-obj ective Facility Layout Problem in Dynamic Cellular Manufacturing
عنوان مقاله: Using Multi-objective Ant Colony Optimization Algorithm to Solve a Multi-obj ective Facility Layout Problem in Dynamic Cellular Manufacturing
شناسه ملی مقاله: IIEC14_015
منتشر شده در چهاردهمین کنفرانس بین المللی مهندسی صنایع در سال 1396
شناسه ملی مقاله: IIEC14_015
منتشر شده در چهاردهمین کنفرانس بین المللی مهندسی صنایع در سال 1396
مشخصات نویسندگان مقاله:
navid darvish ghaderi - MSc of Industrial Engineering, Babol, Iran
ramezan nemati keshteli - Department of Industrial Engineering, Faculty ۰fEngineering-East ۰f Guilan, Guilan university, Vajargah, Iran
خلاصه مقاله:
navid darvish ghaderi - MSc of Industrial Engineering, Babol, Iran
ramezan nemati keshteli - Department of Industrial Engineering, Faculty ۰fEngineering-East ۰f Guilan, Guilan university, Vajargah, Iran
In cellular production, the production system is aimed at transforming several subsystems into a cell in order to produce similar products in a cell with a higher efficiency. In this paper, a multi-objective model in the layout-routing problem of cell production with the goal of minimizing costs, maximizing the level of service to customers has been addressed and solved using the meta- heuristic algorithm MOACO. The results of solving a bi-objective model using this meta-heuristic algorithm with its results in its previous solution method, the meta-heuristic algorithm NSGAII and the Epsilon constraint method showed that MOACO is able to provide better responses than NSGAII for large-scale issues. That is, at approximately equal times, algorithm MOACO was able to produce more accurate and better answers for the second objective function.
کلمات کلیدی: Cellular Production; Multi-objective Model; Meta Heuristic Algorithms; MOACO; NSGAII; Epsilon Constraint
صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/760599/