A Multi-objective Sustainable Medicine Supply Chain Network Design Using a Novel Hybrid Multi-objective Metaheuristic Algorithm

Document Type : Original Article

Authors

Department of Industrial Engineering, Yazd University, Yazd, Iran

Abstract

End-of-life products have a severe impact on the ecological system. Potential production policies and distribution strategies for the newly manufactured product have attracted significant attention to sustainable development. Sustainability in supply chain management has much importance to achieve eco-friendly goals. In this study, we have developed sustainable objectives in the supply chain optimization framework with different constraints. The trade-off between economic, environmental and social effects objectives have identified by ensuring the optimal allocation of different products among various levels.  In this regard, a new sustainability multi-objective mixed-integer linear programming mathematical model in the medicine supply chain network is developed. Although the proposed model is an NP-hard problem, we develop a novel hybrid Particle Swarm Optimization and Genetic Algorithm to achieve Pareto solutions. Then, to adjust the important parameters of the algorithms and chose the optimum levels of the significant factors for more efficiency is employed the Taguchi method. The results show that the economic and environmental effects tend to be decreased and the social impacts tend to be increased in the medicine supply chain network which can exhibit the best sustainability performance. The various outcomes of numerical experiments indicate that the proposed solution algorithm is more reliable than other algorithms. The solution methods are complemented with several sensitivity analyses on the input parameters of the model.

Keywords


1.     Singh, S.K. and Goh, M., "Multi-objective mixed integer programming and an application in a pharmaceutical supply chain", International Journal of Production Research,  Vol. 57, No. 4, (2019), 1214-1237. Doi: 10.1080/00207543.2018.1504172
2.     Weraikat, D., Zanjani, M.K. and Lehoux, N., "Improving sustainability in a two-level pharmaceutical supply chain through vendor-managed inventory system", Operations Research for Health Care,  Vol. 21, (2019), 44-55. Doi: pii/S2211692318300572
3.     Chung, S.H. and Kwon, C., "Integrated supply chain management for perishable products: Dynamics and oligopolistic competition perspectives with application to pharmaceuticals", International Journal of Production Economics,  Vol. 179, (2016), 117-129. Doi: pii/S0925527316300913
4.     Settanni, E., Harrington, T.S. and Srai, J.S., "Pharmaceutical supply chain models: A synthesis from a systems view of operations research", Operations Research Perspectives,  Vol. 4, (2017), 74-95. Doi: pii/S2214716016301105
5.     Weraikat, D., Zanjani, M.K. and Lehoux, N., "Two-echelon pharmaceutical reverse supply chain coordination with customers incentives", International Journal of Production Economics,  Vol. 176, (2016), 41-52. Doi: pii/S0925527316000670
6.     Tavakkoli-Moghaddam, R., Amiri, M. and Azizmohammadi, R., "Solving a redundancy allocation problem by a hybrid multi-objective imperialist competitive algorithm", International Journal of Engineering,  Vol. 26, No. 9, (2013), 1031-1042. Doi: article_72175.html
7.     Mousazadeh, M., Torabi, S.A. and Zahiri, B., "A robust possibilistic programming approach for pharmaceutical supply chain network design", Computers & Chemical Engineering,  Vol. 82, (2015), 115-128. Doi: pii/S0098135415002203
8.     Niaki, S., Najafi, A.A., Zoraghi, N. and Abbasi, B., "Resource constrained project scheduling with material ordering: Two hybridized meta-heuristic approaches", International Journal of Engineering,  Vol. 28, No. 6, (2015), 896-902. Doi: article_72530.html
9.     Zahiri, B., Zhuang, J. and Mohammadi, M., "Toward an integrated sustainable-resilient supply chain: A pharmaceutical case study", Transportation Research Part E: Logistics and Transportation Review,  Vol. 103, (2017), 109-142. Doi: pii/S1366554517300509
10.   Fathollahi-Fard, A.M., Ahmadi, A., Goodarzian, F. and Cheikhrouhou, N., "A bi-objective home healthcare routing and scheduling problem considering patients’ satisfaction in a fuzzy environment", Applied Soft Computing,  Vol. 93, (2020), 106385. Doi:  pii/S1568494620303252
11.   Fakhrzad, M., Talebzadeh, P. and Goodarzian, F., "Mathematical formulation and solving of green closed-loop supply chain planning problem with production, distribution and transportation reliability", International Journal of Engineering, Transactions C: Aspects, Vol. 31, No. 12, (2018), 2059-2067. Doi: article_82271.html
12.   Crum, M., Poist, R., Carter, C.R. and Easton, P.L., "Sustainable supply chain management: Evolution and future directions", International Journal of Physical Distribution & Logistics Management, (2011), Doi: 10.1108/09600031111101420/full/html
13.   Seuring, S., "A review of modeling approaches for sustainable supply chain management", Decision Support Systems,  Vol. 54, No. 4, (2013), 1513-1520. Doi: pii/S0167923612001741
14.   Brandenburg, M., Govindan, K., Sarkis, J. and Seuring, S., "Quantitative models for sustainable supply chain management: Developments and directions", European Journal of Operational Research,  Vol. 233, No. 2, (2014), 299-312. Doi: pii/S037722171300787X
15.   Zhang, S., Lee, C.K.M., Wu, K. and Choy, K.L., "Multi-objective optimization for sustainable supply chain network design considering multiple distribution channels", Expert Systems with Applications,  Vol. 65, (2016), 87-99. Doi: pii/S0957417416304365
16.   Tsao, Y.-C., Thanh, V.-V., Lu, J.-C. and Yu, V., "Designing sustainable supply chain networks under uncertain environments: Fuzzy multi-objective programming", Journal of Cleaner Production,  Vol. 174, (2018), 1550-1565. Doi: pii/S0959652617325763
17.   Pishvaee, M.S. and Razmi, J., "Environmental supply chain network design using multi-objective fuzzy mathematical programming", Applied Mathematical Modelling,  Vol. 36, No. 8, (2012), 3433-3446. Doi: S0307904X11006615
18.   Lin, K.-P., Tseng, M.-L. and Pai, P.-F., "Sustainable supply chain management using approximate fuzzy dematel method", Resources, Conservation and Recycling,  Vol. 128, (2018), 134-142. Doi: pii/S0921344916303421
19.   Ahmadi, A., Mousazadeh, M., Torabi, S.A. and Pishvaee, M.S., Or applications in pharmaceutical supply chain management, in Operations research applications in health care management. 2018, Springer.461-491. Doi: 10.1007/978-3-319-65455-3_18
20.   Hulea, M., Rosu, O., Miron, R. and Aştilean, A., "Pharmaceutical cold chain management: Platform based on a distributed ledger", in 2018 IEEE International Conference on Automation, Quality and Testing, Robotics (AQTR), IEEE. 1-6. Doi: https://ieeexplore.ieee.org/abstract/document/8402709
21.   Nasrollahi, M. and Razmi, J., "A mathematical model for designing an integrated pharmaceutical supply chain with maximum expected coverage under uncertainty", Operational Research,  (2019), 1-28. Doi: 10.1007/s12351-019-00459-3
22.   Li, Y., Wei, Z., Zhao, J., Zhang, C. and Liu, Y., "Ambidextrous organizational learning, environmental munificence and new product performance: Moderating effect of managerial ties in china", International Journal of Production Economics,  Vol. 146, No. 1, (2013), 95-105. Doi: pii/S0925527312004744
23.   Yadegari, E., Alem-Tabriz, A. and Zandieh, M., "A memetic algorithm with a novel neighborhood search and modified solution representation for closed-loop supply chain network design", Computers & Industrial Engineering,  Vol. 128, (2019), 418-436. Doi: pii/S0360835218306570
24.   Akbarzadeh, Z., Safaei Ghadikolaei, A., Madhoushi, M. and Aghajani, H., "A hybrid fuzzy multi-criteria decision making model based on fuzzy dematel with fuzzy analytical network process and interpretative structural model for prioritizing larg supply chain practices", International Journal of Engineering,  Vol. 32, No. 3, (2019), 413-423. Doi: article_85659.html
25.   Sadri Esfahani, A. and Fakhrzad, M., "Modeling the time windows vehicle routing problem in cross-docking strategy using two meta-heuristic algorithms", International Journal of Engineering,  Vol. 27, No. 7, (2014), 1113-1126. Doi: article_72345.html
26.   Fakhrzad, M.B. and Goodarzian, F., "A fuzzy multi-objective programming approach to develop a green closed-loop supply chain network design problem under uncertainty: Modifications of imperialist competitive algorithm", RAIRO-Operations Research,  Vol. 53, No. 3, (2019), 963-990. Doi: 2019/03/ro180357/ro180357.html
27.   Goodarzian, F. and Hosseini-Nasab, H., "Applying a fuzzy multi-objective model for a production–distribution network design problem by using a novel self-adoptive evolutionary algorithm", International Journal of Systems Science: Operations & Logistics, (2019), 1-22. Doi: 10.1080/23302674.2019.1607621
28.   Fakhrzad, M.B., Goodarzian, F. and Golmohammadi, A., "Addressing a fixed charge transportation problem with multi-route and different capacities by novel hybrid meta-heuristics", Journal of Industrial and Systems Engineering,  Vol. 12, No. 1, (2019), 167-184. Doi: article_78694.html
29.   Sahebjamnia, N., Goodarzian, F. and Hajiaghaei-Keshteli, M., "Optimization of multi-period three-echelon citrus supply chain problem", Journal of Optimization in Industrial Engineering,  Vol. 13, No. 1, (2020), 39-53. Doi: article_538019.html
30.   Tavakkoli-Moghaddam, R., "Solving a new multi-objective inventory-routing problem by a non-dominated sorting genetic algorithm", International Journal of Engineering,  Vol. 31, No. 4, (2018), 588-596. Doi: article_73156.html
31.   Goodarzian, F., Hosseini-Nasab, H., Muñuzuri, J. and Fakhrzad, M.-B., "A multi-objective pharmaceutical supply chain network based on a robust fuzzy model: A comparison of meta-heuristics", Applied soft computing,  Vol. 92, (2020), 106331. Doi: pii/S1568494620302714