A Hybrid Unconscious Search Algorithm for Mixed-model Assembly Line Balancing Problem with SDST, Parallel Workstation and Learning Effect

سال انتشار: 1399
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 520

فایل این مقاله در 18 صفحه با فرمت PDF قابل دریافت می باشد

استخراج به نرم افزارهای پژوهشی:

لینک ثابت به این مقاله:

شناسه ملی سند علمی:

JR_JOIE-13-2_009

تاریخ نمایه سازی: 26 شهریور 1399

چکیده مقاله:

Due to the variety of products, simultaneous production of different models has an important role in production systems. Moreover, considering the realistic constraints in designing production lines attracted a lot of attentions in recent researches. Since the assembly line balancing problem is NP-hard, efficient methods are needed to solve this kind of problems. In this study, a new hybrid method based on unconscious search algorithm (USGA) is proposed to solve mixed-model assembly line balancing problem considering some realistic conditions such as parallel workstation, zoning constraints, sequence dependent setup times and learning effect. This method is a modified version of the unconscious search algorithm which applies the operators of genetic algorithm as the local search step. Performance of the proposed algorithm is tested on a set of test problems and compared with GA and ACOGA. The experimental results indicate that USGA outperforms GA and ACOGA.

کلیدواژه ها:

نویسندگان

Moein Asadi-Zonouz

Department of Industrial ans Systems Engineering, Tarbiat Modares University, Tehran, Iran

Majid Khalili

Department of Industrial Engineering, Islamic Azad University Karaj Branch,Alborz,Iran

Hamed Tayebi

Department of Industrial Engineering, Islamic Azad University Karaj Branch, Alborz, 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 :
  • Akpınar, S., & Bayhan, G. M. (2011). A hybrid genetic ...
  • AkpıNar, S., Bayhan, G. M., & Baykasoglu, A. (2013). Hybridizing ...
  • Akpinar, Ş., & Baykasoğlu, A. (2014a). Modeling and solving mixed-model ...
  • Akpinar, Ş., & Baykasoğlu, A. (2014b). Modeling and solving mixed-model ...
  • Andres, C., Miralles, C., & Pastor, R. (2008). Balancing and ...
  • Ardjmand, E., & Amin-Naseri, M. R. (2012). Unconscious search-a new ...
  • Ardjmand, E., Park, N., Weckman, G., & Amin-Naseri, M. R. ...
  • Biskup, D. (1999). Single-machine scheduling with learning considerations. European Journal ...
  • Bowman, E. H. (1960). Assembly-line balancing by linear programming. Operations ...
  • Buxey, G. (1974). Assembly line balancing with multiple stations. Management ...
  • Cohen, Y., Vitner, G., & Sarin, S. C. (2006). Optimal ...
  • Delice, Y., Aydoğan, E. K., Özcan, U., & İlkay, M. ...
  • Fattahi, P., & Askari, A. (2018). A Multi-objective mixed-model assembly ...
  • A Multi-Objective Particle Swarm Optimization for Mixed-Model Assembly Line Balancing with Different Skilled Workers [مقاله ژورنالی]
  • Gansterer, M., & Hartl, R. F. (2018). One-and two-sided assembly ...
  • Gokcen, H., & Erel, E. (1997). A goal programming approach ...
  • Gökċen, H., & Erel, E. (1998). Binary integer formulation for ...
  • Gunther, R. E., Johnson, G. D., & Peterson, R. S. ...
  • Hamta, N., Ghomi, S. F., Jolai, F., & Shirazi, M. ...
  • Hamzadayi, A., & Yildiz, G. (2012). A genetic algorithm based ...
  • Haq, A. N., Rengarajan, K., & Jayaprakash, J. (2006). A ...
  • Hyun, C. J., Kim, Y., & Kim, Y. K. (1998). ...
  • Kilbridge, M. D., & Wester, L. (1961). A heuristic method ...
  • Koltai, T., & Kalló, N. (2017). Analysis of the effect ...
  • Li, Z., Janardhanan, M. N., Tang, Q., & Ponnambalam, S. ...
  • Lolli, F., Balugani, E., Gamberini, R., & Rimini, B. (2017). ...
  • Manavizadeh, N., Hosseini, N.-s., Rabbani, M., & Jolai, F. (2013). ...
  • Moradi, H., & Zandieh, M. (2013). An imperialist competitive algorithm ...
  • Mosheiov, G. (2001). Scheduling problems with a learning effect. European ...
  • Nourmohammadi, A., Zandieh, M., & Tavakkoli-Moghaddam, R. (2013). An imperialist ...
  • Özcan, U., & Toklu, B. (2010). Balancing two-sided assembly lines ...
  • Rabbani, M., Aliabadi, L., & Farrokhi-Asl, H. (2019). A Multi-Objective ...
  • Seyed-Alagheband, S., Ghomi, S. F., & Zandieh, M. (2011). A ...
  • Thomopoulos, N. T. (1967). Line balancing-sequencing for mixed-model assembly. Management ...
  • Thomopoulos, N. T. (1970). Mixed model line balancing with smoothed ...
  • Toksarı, M. D., İşleyen, S. K., Güner, E., & Baykoç, ...
  • Toksarı, M. D., İşleyen, S. K., Güner, E., & Baykoç, ...
  • Tonge, F. M. (1960). A heuristic program for assembly line ...
  • Vilarinho, P. M., & Simaria, A. S. (2002). A two-stage ...
  • Yagmahan, B. (2011). Mixed-model assembly line balancing using a multi-objective ...
  • Productivity Improvement through Line Balancing by Using Simulation Modeling [مقاله ژورنالی]
  • Yolmeh, A., & Kianfar, F. (2012). An efficient hybrid genetic ...
  • Yuan, B., Zhang, C., Shao, X., & Jiang, Z. (2015). ...
  • Zhong, Y., Deng, Z., & Xu, K. (2019). An effective ...
  • نمایش کامل مراجع