Multi-period Multi-level Supply Chain Network Design in Agile Manufacturing with Tabu Search Algorithm
Subject Areas : Research and Development Managementelahe salari 1 , mohammadreza shahraki 2 * , abdollah sharifi 3
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Keywords: Supply Chain Network Design Multi-level Meta-heuristic Tabu Search Algorithm Strategic Oscillation,
Abstract :
Supply chain network design includes key decisions that have a major impact on the supply chain operational structure. Efficient supply chain design improves performance in organizations. This has led to the emergence of new concepts in the supply chain issue in the past decade. In this study, the supply chain network design problem in agile organizations has been taken into account with multi-level and multi-period. This problem is considered under conditions of having multiple customers with a high demand volume. The decisions include the selection of companies at each level, the amount of production, storage and transportation of each company. The problem has been modeled to integrate all decision variables with the goal of minimizing overall operating costs across the entire supply chain and Satisfaction of customers' complete demand and Satisfaction with them. Since multi-period multi-level supply chain design problem solving is one of the NP-Hard issues in uncertainty conditions, it is better to use innovative and meta-algorithms to reduce problem solving time. For this reason, the algorithm for banning search algorithms, which is one of the meta-algorithms, has been used to solve the model. The results of this research show that as the number of problem-solving repetitions increases, answers with less than 3% of the difference between the optimal answer are achieved. The search algorithm is forbidden to get the optimal response compared to the Lagrange algorithm.
1- عقیانی مونا، جبارزاده آرمین، سجادی جعفر. "ارائه یک مدل بهینهسازی استوار جهت طراحی شبکه زنجیره تأمین خون در شرایط بحران با در نظر گرفتن قابلیت اطمینان". نشریه مهندسی و مدیریت کیفیت، ۱۳۹۴.
2- زاهدی علی، صالحی امیری امیرحسین، سرور جواد، اکبری حسینعلی. "طراحی شبکه زنجیره تأمین چند محصولی، چند سطحی، حلقه بسته تحت شرایط کاملاً فازی". هشتمین کنفرانس بینالمللی انجمن ایرانی تحقیق در عملیات، ۱۳۹۴.
3- فتاحی، پرویز. "الگوریتمهای فراابتکاری". انتشارات دانشگاه بوعلی سینا. سال ۱۳۹۳.
4- Pan, F., Nagi, R. “Multi-echelon supply chain network design in agile manufacturing”. Omega, vol. 41, pp. 969-983, 2013.
5- Farahani, R., Rezapour, Sh., Drezner, T., Fallah, S. “Competitive supply chain network design: An overview of classifications, models, solution techniques and applications”. Omega, vol. 45, pp. 92-118, 2014.
6- Pham, T., Yenradee, P. “Optimal Supply Chain Network Design with Process Network and Bom under uncertainties: A Cace Study in Toothbrush Industry”. Computers & Industrial Engineering, 2017.
7- Agarwal, A., Shankar, R., Tiwari, M.K. “Modeling agility of supply chain”. Industrimal Marketing Management, vol, 36, pp. 443-457, 2007.
8- Adeleye, E.O., Yusuf, Y.Y. “Towards agile manufacturing: Model of competition and performance outcomes”. International Journal Systems and Management,vol. 1, pp. 93-110, 2006.
9- Jain, N.K., Jain, V.K. “Computer aided process planning for agile manufacturing environment strategy”. Elsevier, pp. 515-534, 2001.
10- Varsei, M. Polyakovskiy, S. ‘Sustainable supply chain network design: A case of the wine industry in Australia”. Omega, vol. 66, pp. 236-247, 2017.
11- Rahmani, D,. Mahoodian, V. “Strategic and operational supply chain network design to reduce carbon emission considering reliability and robustness”. Journal of Cleaner Production, vol. 149, pp. 607-620, 2017.
12- Dehghan, E., Shafiei, M., Amiri, M., Jabbarzadeh, A. “Hybrid robustm stochastic and possibilistic programming for closed-loop supply chain network design” Computers & Industrial Engineering, vol. 123, pp. 220-231, 2018.
13- Subulan, K., Baykasoglu, A. Ozsoydan, F. B. Tasan, A. S. Selim, H. “A case-oriented approach to a lead/ acid battery closed-loop supply chain network design under risk and uncertainty”. Journal of Manufacturing System, vol. 37, pp. 340-361, 2015.
14- Najjartabar-Bisheh, M., Delavari, M., Malmir, B. “Role of third-party companies in a sustainable supply chain design”. International Journal Logistics Systems and Management, vol. 30, pp. 95-112, 2018.
15- Lemmens, S., Decouttere, C., Vandaele, N., Bernuzzi, M. “A review of integrated supply chain network design models: Key issues for vaccine supply chain”. Chemical Engineering Research and Design, vol. 109, pp. 366-384, 2016.
16- Heidari-Fathian, H., Pasandideh, S. H. R. “Green-blood supply chain network design: Robust optimization, bounded objective function & Lagrangian relaxation”. Computers & Industrial Engineering, vol. 122, pp. 95-105, 2018.
17- Altiparmak, F., Karaoglan, I. “An Adaptive tabu-simulated annealing for concave cost transportation problems”. The Journal of the Opevational Research society, vol. 59, pp. 331-341, 2008.
18- Silva, M. R., Cunha, C. B. “A tabu search heuristic for the uncapacitatect single allocation p-hub maximal covering problem”. European Journal of Operational Research, vol. 262, pp. 954-965, 2017.
19- Pham, D. T., Karaboga, D. “Intelligent Optimisation Techniques: Genetic Algorithm, Tabu Search, Simulated Annealing and Neural Networks”. Springer, 1999.
20- Sun, M. “Solving the uncapacitated facility location problem using tabu search”. Computers & Operations Research,vol. 33, pp. 2563–2589, 2006
21- http://faradars.org
22- Jabbarzadeh, A., Haughton, M., Khosrojerdi, A. “Closed-loop Supply Chain Network Design under Disruption Risks: A Robust Approach with Real World Application”. Computers & Industrial Engineering, vol. 118, pp. 178-191, 2018.
23- Eskandarpour, M., Dejax, P., Peton, O. “A large neigh borhood search heuristic for supply chain network design”. Computers & Operations Research, vol. 80. pp.23-37.
24- Saghaeeian, A., Ramezanian, R. “An efficient hybrid genetic algorithm for multi-product competitive supply chain network design with price dependent demand”. Applied Soft Computing, vol. 71, pp.872-893.
25- Alavi, S.H., Jabbarzadeh, A., “Supply chain network design using trade credit and bank credit: A robust optimization model with real world application”. Computers & Industrial Engineering, vol. 125, pp. 69-86, 2018.
26- Zhen, L., et al. “Copacitated Closed-loop supply chain network design under uncertainty”. Advanced Engineering Informatics, vol. 38, pp.306-315.
27- Fathollahi-fard, A.M., Hajiaghaei-Keshteli, M., Mirjalili, S. A. “Multi-objective stochastic closed-loop supply chain network design with social considerations”. Applied Soft Computing, vol. 71, pp.505-525.