Multi-Objective Closed-loop Supply Chain Considering Vehicles and Solving by New Approaches in Metaheuristics

Document Type : Industry Article

Authors

1 Mazandaran University of Science and Technology

2 Khodadad 4

Abstract

Recently, concerns have been raised about the environmental and social impacts of commercial activities. Also, most papers on the design of the supply chain network, focus on economic performance. Recently, some studies have considered environmental and social dimensions. There are still some gaps in modelling social impacts along with environmental and economic impacts. In this study, a multi-objective probabilistic model for designing a sustainable closed-loop logistics network is presented under uncertainty. The goals of this model consist of cost reduction, increasing social impact and decreasing environmental impacts. Then the model was solved not only using well-known Metaheuristic algorithms including genetic algorithm and Simulated Annealing (SA) algorithm, but also new whale optimization algorithm along with its improved combination method was used. Performance of algorithms was compared through examining different experiments and designed test problems. They compared in different situations and some important criteria. The results show the superiority of the whale optimization algorithm.

Keywords


1[ یک مدل چندهدفه استوار برای طراحی زنجیره تأمین با « ، احمد ماکوئی، حمید صفاری، میرسامان پیشوایی و وحید محمودیان
مجله مدلسازی در مهندسی، دانشگاه سمنان، دوره ،» درنظرگیری جریان رو به جلو و عقب و مسئولیتپذیری اجتماعی 14 ، شماره 47 ،
پاییز 1395 ، صفحه 171 - 185 .
[2] A.M.F. Fard and M. Hajiaghaei-Keshteli, "A tri-level location-allocation model for forward/reverse supply chain", Applied Soft Computing, Vol. 62, 2018, pp. 328-346.
84 بررسی مدل احتمالی چندهدفه برای مسئله زنجیرة تأمین حلقه بستة پایدار با در نظرگرفتن...
مجله مدل سازی در مهندسی سال هفدهم، شماره 59 ، زمستان 1398
[3] K. Govindan and H. Soleimani, "A review of reverse logistics and closed-loop supply chains. a journal of cleaner production focus", Journal of Cleaner Production, Vol. 142, 2017, pp. 371-384
[4] M. Zhalechian, R. Tavakkoli-Moghaddam, B. Zahiri and M. Mohammadi, "Sustainable design of a closed-loop location-routing-inventory supply chain network under mixed uncertainty", Transportation Research Part E: Logistics and Transportation Review, Vol. 89, 2016, pp. 182-214
[5] M. Zohal and H. Soleimani, "Developing an ant colony approach for green closed-loop supply chain network design: a case study in gold industry", Journal of Cleaner Production, Vol. 133, 2016, pp. 314-337.
[6] M.S. Pishvaee, J. Razmi and S.A. Torabi, "An accelerated Benders decomposition algorithm for sustainable supply chain network design under uncertainty: A case study of medical needle and syringe supply chain", Transportation Research Part E: Logistics and Transportation Review, Vol. 67, 2014, pp. 14-38
[7] Y.Y. Cui, Z. Guan, U. Saif, L. Zhang, F. Zhang and J. Mirza, "Close Loop Supply Chain Network Problem with Uncertainty in Demand and Returned Products: Genetic Artificial Bee Colony Algorithm Approach", Journal of Cleaner Production, Article in Press, 2018.
[8] D.M. Lambert, J.R. Stock and L.M. Ellram, "Fundamentals of logistics management", McGraw-Hill/Irwin, Vol. 44, 1998, pp. 243-277.
[9] K. Devika, A. Jafarian and V. Nourbakhsh, "Designing a sustainable closed-loop supply chain network based on triple bottom line approach: A comparison of metaheuristics hybridization techniques", European Journal of Operational Research, Vol. 235, No. 3, 2014, pp. 594-615.
[10] H. Soleimani and G. Kannan, "A hybrid particle swarm optimization and genetic algorithm for closed-loop supply chain network design in large-scale networks", Applied Mathematical Modelling, Vol. 39, No. 14, 2016, 3990-4012
[11] H. Soleimani, K. Govindan, H. Saghafi and H. Jafari, "Fazzy multi-objective sustainable and green closed-loop supply chain network design", Computers and Industrial engineering, Vol. 109, 2017, pp. 191-203
[12] M. Mousazadeh, S.A. Torabi and M.S. Pishvaee, "Green and reverse logistics management under fuzziness. In Supply Chain Management under Fuzziness", Springer Berlin Heidelberg Vol. 23, 2014, pp. 607-637.
[13] R. Babazadeh, J. Razmi, M.S. Pishvaee and M. Rabbani, "A sustainable second-generation biodiesel supply chain network design problem under risk", Omega, Vol. 66, 2017, pp. 258-277.
[14] A. Hasani and A. Khosrojerdi, "Robust global supply chain network design under disruption and uncertainty considering resilience strategies: A parallel memetic algorithm for a real-life case study", Transportation Research Part E: Logistics and Transportation Review, Vol. 87, 2016, pp. 20-52. [15] A.M.F. Fard, F. Gholian-Jouybari, M.M. Paydar and M. Hajiaghaei-Keshteli, "A Bi-objective stochastic closed-loop supply chain network design problem considering downside risk", Industrial Engineering & Management Systems, Vol. 16, No. 1, 2017, pp. 342-62.
[16] R. Sreedevi and H. Saranga, "Uncertainty and supply chain risk: The moderating role of supply chain flexibility in risk mitigation", International journal of production Economics, Vol. 193, 2017, pp. 332-342
[17] M.C. Fonseca, A. García-Sánchez, M. Ortega-Mier and F. Saldanha-da-Gama, "A stochastic bi-objective location model for strategic reverse logistics", Top, Vol. 18, No. 1, 2010, pp. 158-184.
[18] S. Elhedhli and R. Merrick, "Green supply chain network design to reduce carbon emissions", Transportation Research Part D: Transport and Environment, Vol. 17, No. 5, 2012, pp. 370-379.
[19] M.S. Pishvaee, S.A. Torabi and J. Razmi, "Credibility-based fuzzy mathematical programming model for green logistics design under uncertainty", Computers & Industrial Engineering, Vol. 62, No. 2, 2012, pp. 624-632.
[20] B. Vahdani, R. Tavakkoli-Moghaddam, M. Modarres and A. Baboli, "Reliable design of a forward/reverse logistics network under uncertainty: a robust-M/M/c queuing model", Transportation Research Part E: Logistics and Transportation Review, Vol. 48, No. 6, 2012, pp. 1152-1168.
[21] M. Talaei, B.F. Moghaddam, M.S. Pishvaee, A. Bozorgi-Amiri and S. Gholamnejad, "A robust fuzzy optimization model for carbon-efficient closed-loop supply chain network design problem: a numerical illustration in electronics industry", Journal of Cleaner Production, Vol. 113, 2016, pp. 662-673
عبدی و حاجیآقایی کشتلی 85
مجله مدل سازی در مهندسی سال هفدهم، شماره 59 ، زمستان 1398
[22] M. Fleischmann, P. Beullens, J.M. BLOEMHOF‐RUWAARD and L.N. Wassenhove, "The impact of product recovery on logistics network design", Production and operations management, Vol. 10, No. 2, 2001, pp. 156-173.
]23[ ارزیابی و مقایسه الگوریتمهای بهینهسازی ژنتیک، شبیهسازی تبرید و « ، فرشاد حکیمپور، سیامک طلعت اهری و ابوالفضل رنجبر
مجلة مدلسازی در مهندسی، دانشگاه سمنان، دوره ،») فاختهها در مکانیابی رقابتی تسهیلات )مطالعه موردی: بانکها 15 ، شماره 48 ،
1396 ، صفحه 231 - 246 .
[24] M. Hajiaghaei-Keshteli and M. Aminnayeri, "Solving the integrated scheduling of production and rail transportation problem by Keshtel algorithm", Applied Soft Computing, Vol. 25, 2014, pp. 184-203.
[25] S. Sadeghi-Moghaddam, M. Hajiaghaei-Keshteli and M. Mahmoodjanloo, "New approaches in metaheuristics to solve the fixed charge transportation problem in a fuzzy environment", Neural Computing and Applications, Vol. 68, 2017, pp. 1102-11023.
[26] S. Mirjalili and A. Lewis, "The whale optimization algorithm", Advances in Engineering Software, Vol. 95, 2016, pp. 51-67.
[27] R.H. Mayers, C.D. Montgomery and C.M. Anderson-Cook, Response surface methodology, Hoboken, New Jersey: John Wiley & Sons, Vol. 2, 2009, pp. 38-45.
]28 [ مدلسازی چندهدفه مسئله تخصیص گیت با استفاده از الگوریتم « ، ساناز خطیبی. مرتضی خاکزار بفروئی و مرتضی رحمانی NSGA-II مجلة مدلسازی در مهندسی، دوره ،» و محدودیت اپسیلون 15 ، شماره 51 ، 1396 ، صفحه 397 - 410 .
[29] M. Hajiaghaei-Keshteli and A.M. Fathollahi-Fard, "A set of efficient heuristics and metaheuristics to solve a two-stage stochastic bi-level decision-making model for the distribution network problem", Computers & Industrial Engineering, vol. 123, 2018, pp. 378-395. [30] A.M. Fathollahi-Fard, M. Hajiaghaei-Keshteli and S. Mirjalili, "Hybrid optimizers to solve a tri-level programming model for a tire closed-loop supply chain network design problem", Applied Soft Computing. Vol. 70, 2018, pp. 701-722. [31] A.M. Fathollahi-Fard, M. Hajiaghaei-Keshteli and S. Mirjalili, "Multi-objective stochastic closed-loop supply chain network design with social considerations", Applied Soft Computing, Vol. 71, 2018, pp. 505-525. [32] A.M. Fathollahi-Fard and M. Hajiaghaei-Keshteli, "A stochastic multi-objective model for a closed-loop supply chain with environmental considerations", Applied Soft Computing, Vol. 69, 2018, pp. 232-249. [33] A. Samadi, N. Mehranfar, A.M. Fathollahi Fard and M. Hajiaghaei-Keshteli, "Heuristic-based metaheuristic to address a sustainable supply chain network design problem", Journal of Industrial and Production Engineering. Vol. 35, No. 2, 2018, pp. 102-117. [34] Y. Fu, Y.G. Tian, A.M. Fathollahi-Fard, A. Ahmadi and C. Zhang, "Stochastic multi-objective modelling and optimization of an energy-conscious distributed permutation flow shop scheduling problem with the total tardiness constraint", Journal of Cleaner Production, Vol. 226, 2019, pp. 515-525.