A Hybrid Genetic Algorithm technique for Scheduling Flexible Manufacturing Cells

سال انتشار: 1387
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 2,303

فایل این مقاله در 15 صفحه با فرمت PDF قابل دریافت می باشد

این مقاله در بخشهای موضوعی زیر دسته بندی شده است:

استخراج به نرم افزارهای پژوهشی:

لینک ثابت به این مقاله:

شناسه ملی سند علمی:

IIEC06_192

تاریخ نمایه سازی: 8 مهر 1387

چکیده مقاله:

The aim of this paper is scheduling of flexible manufacturing cell (FMC). These types of production systems combine merit of job shop production and flow shop production systems. FMS Scheduling belongs to the class of problems that are proved to be NP-hard. This paper, first a mathematical model, based on the Liu and McCarthy’s [1] model with a new assumption, is presented and then a hybrid genetic algorithm technique is designed to schedule machines and AGV simultaneously. To generate schedules from a given chromosome, four priority dispatching rules (PDR) are considered. The completion time or makespan is defined as objective function. This algorithm is coded and its results are compared with optimum value obtained from MILP model. The experimental results show that this proposed method performs well in terms of efficiency and quality of solutions.

نویسندگان

M. T. Taghavi Fard

Graduate School of Industrial Engineering, Islamic Azad University-Tehran South Branch, Tehran, Iran

F. Rayat Sanati

Department of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran

M. Heydar

Graduate School of Industrial Engineering, Islamic Azad University-Tehran South Branch, Tehran, Iran

مراجع و منابع این مقاله:

لیست زیر مراجع و منابع استفاده شده در این مقاله را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود مقاله لینک شده اند :
  • Liu, J., and MacCarthy, B. L., A global MILP model ...
  • Groover, M.P., Automation, Production Systems, and Compute r-Integrated Manufacturing, 3[ ...
  • Jerald, J., Asokan, P., Saravanan, R., and Rani, A. D. ...
  • International Journal of Advanced Manufactu ring Technology, 29(5) 584-589 (2005). ...
  • Tung, L. F., Lin, L. and Nagi, R., Multiple-obj ective ...
  • Noorul Haq, A., Karthikeyan, T., and Dinesh, M., Scheduling decision ...
  • Sankar, S. S., Ponnambal an, S. G., and Rajendran, C., ...
  • Kim, K. W., Yamazaki, G., Lin, L. and Gen, M., ...
  • Chan, F. T. S. and Chan, H. K., Dynamic scheduling ...
  • Reddy, B. S. P., and Rao, C. S. P., A ...
  • Maccarthy, B. L. and Liu, J., A new classification for ...
  • Ahluwalia, R. S. and Ping, J., A distributed approach to ...
  • Jiang, J. and Hsiao, W. C., Mathematical programming for the ...
  • Sridharan, R. and Babu, A. S., Multi-level scheduling decisions in ...
  • Prabaharan, T., Nakkeeran, P. R. and Jawahar, N., Sequencing and ...
  • Ulsoy, G., Serifoglu, F. S. and Bilge, U., A genetic ...
  • Logendran, R. and Sonthinen, A., A tabu search-based approach for ...
  • Masatoshi, Sakawa, Genetic algorithms and fuzzy _ ulti-objective optimization, Kluwer ...
  • Baker, K. R., Introduction to sequencing and scheduling, New York, ...
  • Gen, M. and Cheng, R., Genuetic algorithms and engineering optimization, ...
  • Gen, M. and Cheng, R., Genetic algorithms and engineering design, ...
  • نمایش کامل مراجع