مدلسازی یکپارچه برنامه‌ریزی و زمانبندی تولید و نگه‌داری تعمیرات در محیط جریان کارگاهی ترکیبی

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری، مهندسی صنایع، دانشگاه علوم و فنون مازندران. بابل. ایران

2 دانشیار، گروه مهندسی صنایع، دانشگاه علوم و فنون مازندران، بابل، ایران

3 استاد، گروه مهندسی صنایع، دانشگاه علوم و فنون مازندران، بابل، ایران

4 استاد، گروه مهندسی صنایع، دانشگاه الزهرا، تهران، ایران

چکیده

یکپارچه‌سازی زمانبندی و برنامه‌ریزی تولید از تصمیمات مهم در هر سازمان تولیدی است که منجر به افزایش اثربخشی مدیریت عملیات می‌شود. تصمیمات بلندمدت برنامه‌ریزی تولید (تعیین مقدار تولید، سطح موجودی و غیره) و تصمیمات کوتاه مدت عملیاتی زمانبندی (ترتیب پردازش کارها و عملیات نت) تاثیر دوطرفه و مستقیم بر یکدیگر دارند. در این مقاله مدل ریاضی جدیدی برای تصمیم‌گیری همزمان برنامه‌ریزی و زمانبندی تولید با هدف حداقل کردن مجموع هزینه‌ها، زمان و دیرکرد در محیط جریان کارگاهی ترکیبی ارائه می‌شود. مفهوم نت ناکامل و در نظر گرفتن چند نوع منبع نگهداری تعمیرات در مدل پیشنهادی ارائه شده است. دو الگوریتم تکاملی فراابتکاری چندهدفه مبتنی بر الگوریتم جستجوی هماهنگی و روش حل دقیق اپسیلون-محدودیت برای حل مدل پیشنهادی ارائه شده است که فضای حل تصمیم‌گیری را به روشی مستمر جستجو می‌کنند. بدین منظور نمونه مسائلی مرتبط با مقاله پیشین ارائه شد و از سه معیار عملکردی تعداد حلهای پارتو، متوسط فاصله ایده‌آل و پراکندگی حلهای نامغلوب برای مقایسه نتایج حاصل از الگوریتمهای فراابتکاری استفاده شد. نتایج نشان دهنده مزایا و اثربخشی روشهای استفاده شده در تعیین جواب بهینه پارتو برای مسائل بهینه‌سازی است.

کلیدواژه‌ها

عنوان مقاله [English]

Integrated production planning and scheduling with maintenance constraints in hybrid flow shop environment

نویسندگان [English]

  • iman rastgar 1
  • Javad Rezaeian 2
  • iraj mahdavi 3
  • Parviz Fattahi 4
1 PhD student, industrial engineering, Mazandaran University of Science and Technology. Babylon Iran
2 Associate Professor, Department of Industrial Engineering, Mazandaran University of Science and Technology, Babol, Iran
3 Professor, Department of Industrial Engineering, Mazandaran University of Science and Technology, Babol, Iran
4 Professor, Department of Industrial Engineering, Al-Zahra University, Tehran, Iran
چکیده [English]

Integrating production scheduling and scheduling is one of the most important decisions in any production organization that leads to increase the effectiveness of operations management. Long-term production planning decisions (determination of production quantity, inventory level, etc.) and short-term operational scheduling decisions (order of work processing and maintenance activities) have a direct effect on each other. In this study, a new mathematical model for simultaneous decision making of production planning and scheduling is presented with the aim of minimizing the total costs, time and delay in the hybrid flowshop. The concept of imperfect maintenance and considering several types of repair maintenance sources is presented in the proposed model. Two multi-objective meta-heuristic evolutionary algorithms based on the harmony search algorithm and the exact Epsilon-constraint solution method are proposed to solve the proposed model, which continuously searches the decision-making solution space. For this purpose, a sample of test problems of literature review and three performance criteria of Pareto number of solutions, mean ideal distance and Spacing metric are used to compare the results of meta-heuristic algorithms. The results show the advantages and effectiveness of the methods used in determining the Pareto optimal solution for optimization problems.

کلیدواژه‌ها [English]

  • Integrated production and scheduling
  • Hybrid flowshop
  • Imperfect maintenance
  • Harmony search algorithm

مراجع

[1]    parsaei M,  nili ahmadabadi M. Prioritizing Maintenance Strategies with a Combination Approach DEMATEL-ANP-COPRAS in Auto Parts Manufacturing Industry Case Study: Milad Company of Qom, Journal of Modern Research in Decision Making, ,Volume: 1 Issue: 2, 2018- 29:50.
[2]    Ramezanian, R., M. Saidi-Mehrabad, and E. Teimoury, A mathematical model for integrating lot-sizing and scheduling problem in capacitated flow shop environments. The International Journal of Advanced Manufacturing Technology, 2013. 66(1-4): p. 347-361.
[3]    Gómez Urrutia, E.D., R. Aggoune, and S. Dauzère-Pérès, Solving the integrated lot-sizing and job-shop scheduling problem. International Journal of Production Research, 2014. 52(17): p. 5236-5254.
[4]    Ramezanian, R., S.F. Sanami, and M.S. Nikabadi, A simultaneous planning of production and scheduling operations in flexible flow shops: case study of tile industry. The International Journal of Advanced Manufacturing Technology, 2016: p. 1-15.
[5]    Najid, N.M., M. Alaoui-Selsouli, and A. Mohafid, An integrated production and maintenance planning model with time windows and shortage cost. International journal of production research, 2011. 49(8): p. 2265-2283.
[6]    Aghezzaf, E.-H. and N.M. Najid, Integrated production planning and preventive maintenance in deteriorating production systems. Information Sciences, 2008. 178(17): p. 3382-3392.
[7]    Nourelfath, M. and E. Châtelet, Integrating production, inventory and maintenance planning for a parallel system with dependent components. Reliability Engineering & System Safety, 2012. 101: p. 59-66.
[8]    Ramezanian, R., M. Saidi-Mehrabad, and P. Fattahi, MIP formulation and heuristics for multi-stage capacitated lot-sizing and scheduling problem with availability constraints. Journal of Manufacturing Systems, 2013. 32(2): p. 392-401.
[9]    Fitouhi, M.-C. and M. Nourelfath, Integrating noncyclical preventive maintenance scheduling and production planning for multi-state systems. Reliability Engineering & System Safety, 2014. 121: p. 175-186.
[10]    Aghezzaf, E.H., M.A. Jamali, and D. Ait-Kadi, An integrated production and preventive maintenance planning model. European journal of operational research, 2007. 181(2): p. 679-685.
[11]    Yalaoui, A., K. Chaabi, and F. Yalaoui, Integrated production planning and preventive maintenance in deteriorating production systems. Information Sciences, 2014. 278: p. 841-861.
[12]    Wolosewicz, C., S. Dauzère-Pérès, and R. Aggoune, A Lagrangian heuristic for an integrated lot-sizing and fixed scheduling problem. European Journal of Operational Research, 2015. 244(1): p. 3-12.
[13]    An, Y.-W. and H.-S. Yan, Lagrangean relaxation approach to joint optimization for production planning and scheduling of synchronous assembly lines. International Journal of Production Research, 2016. 54(22): p. 6718-6735.
[14]    Menezes, G.C., G.R. Mateus, and M.G. Ravetti, A branch and price algorithm to solve the integrated production planning and scheduling in bulk ports. European Journal of Operational Research, 2017. 258(3): p. 926-937.
[15]    Cho, H.-M. and I.-J. Jeong, A two-level method of production planning and scheduling for bi-objective reentrant hybrid flow shops. Computers & industrial engineering, 2017. 106: p. 174-181.
[16]    Mahdieh, M., A. Clark, and M. Bijari, A novel flexible model for lot sizing and scheduling with non-triangular, period overlapping and carryover setups in different machine configurations. Flexible Services and Manufacturing Journal, 2018. 30(4): p. 884-923.
[17]    Hu, Z. and G. Hu, A multi-stage stochastic programming for lot-sizing and scheduling under demand uncertainty. Computers & Industrial Engineering, 2018. 119: p. 157-166.
[18]    Bhosale, K. and P. Pawar, Material flow optimisation of flexible manufacturing system using real coded genetic algorithm (RCGA). Materials Today: Proceedings, 2018. 5(2): p. 7160-7167.
[19]    Alimian, M., V. Ghezavati, and R. Tavakkoli-Moghaddam, New integration of preventive maintenance and production planning with cell formation and group scheduling for dynamic cellular manufacturing systems. Journal of Manufacturing Systems, 2020. 56: p. 341-358.
[20]    Han, J., et al., Integrated production planning and scheduling under uncertainty: A fuzzy bi-level decision-making approach. Knowledge-based systems, 2020. 201: p. 106056.
[21]    Naderi, B. and R. Ruiz, The distributed permutation flowshop scheduling problem. Computers & Operations Research, 2010. 37(4): p. 754-768.
[22]     Khodabandeh M,  Hejazi Taghanaki S.R. Rasti-Barzoki M. A Heuristic Method to Minimize Total Weighted Number of Tardy Jobs and Transportation Costs for an Integrated Production and Distribution Problem with VRP, Journal of Modern Research in Decision Making,Volume: 3 Issue: 3, 2018- 55:78
[23]    Zhang, Z., Q. Tang, and M. Chica, Maintenance costs and makespan minimization for assembly permutation flow shop scheduling by considering preventive and corrective maintenance. Journal of Manufacturing Systems, 2021. 59: p. 549-564.
[24]    Geem, Z.W., J.H. Kim, and G.V. Loganathan, A new heuristic optimization algorithm: harmony search. simulation, 2001. 76(2): p. 60-68.
[25]    Mahdavi, M., M. Fesanghary, and E. Damangir, An improved harmony search algorithm for solving optimization problems. Applied mathematics and computation, 2007. 188(2): p. 1567-1579.
[26]    Deb, K., et al. A fast elitist non-dominated sorting genetic algorithm for multi-objective optimization: NSGA-II. in International conference on parallel problem solving from nature. 2000. Springer.
[27]    Omid A,  Azar A. Nayeri M. D. Mghbel A.  Developing a network Data Envelopment Analysis approach to compare the environmental efficiency of active industries in Tehran, Management Research in Iran, Volume: 3 Issue: 25, 2021- 193:216.
[28]    Tavakkoli-Moghaddam, R., A. Rahimi-Vahed, and A.H. Mirzaei, A hybrid multi-objective immune algorithm for a flow shop scheduling problem with bi-objectives: weighted mean completion time and weighted mean tardiness. Information Sciences, 2007. 177(22): p. 5072-5090.
[29]     Olfat, L.  Total Tardiness Minimization in Flow Shop with Intermediate Due Dates, Management Research in Iran, Volume: 2 Issue: 3, 2018- 25:47.
پژوهش های نوین در تصمیم گیری
دوره 7، شماره 2
تیر 1401
صفحه 1-27

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