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Articles

Applying a fuzzy multi-objective model for a production–distribution network design problem by using a novel self-adoptive evolutionary algorithm

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Pages 1-22 | Received 03 Dec 2018, Accepted 08 Apr 2019, Published online: 14 May 2019

References

  • Amirtaheri, O., Zandieh, M., Dorri, B., & Motameni, A. R. (2017). A bi-level programming approach for production-distribution supply chain problem. Computers & Industrial Engineering, 110, 527–537. doi: 10.1016/j.cie.2017.06.030
  • Archetti, C., Bertazzi, L., Paletta, G., & Speranza, M. G. (2011). Analysis of the maximum level policy in a production-distribution system. Computers & Operations Research, 38(12), 1731–1746. doi: 10.1016/j.cor.2011.03.002
  • Bandyopadhyay, S., & Bhattacharya, R. (2014). Solving a tri-objective supply chain problem with modified NSGA-II algorithm. Journal of Manufacturing Systems, 33(1), 41–50. doi: 10.1016/j.jmsy.2013.12.001
  • Chopra, S., & Meindl, P. (2007). Supply chain management. In Strategy, planning & operation. Das summa summarum des management (pp. 265–275).
  • De, A., Choudhary, A., & Tiwari, M. K. (2017). Multiobjective approach for sustainable ship routing and scheduling with draft restrictions. IEEE Transactions on Engineering Management, 99, 1–17.
  • Dubois, D., & Prade, H. (2012). Possibility theory: An approach to computerized processing of uncertainty (Vol. 34, pp. 67–79). Berlin: Springer Science & Business Media.
  • Fahimnia, B., Farahani, R. Z., Marian, R., & Luong, L. (2013). A review and critique on integrated production–distribution planning models and techniques. Journal of Manufacturing Systems, 32(1), 1–19. doi: 10.1016/j.jmsy.2012.07.005
  • Fard, A. M. F., Gholian-Jouybari, F., Paydar, M. M., & Hajiaghaei-Keshteli, M. (2017). A bi-objective stochastic closed-loop supply chain network design problem considering downside risk. Industrial Engineering & Management Systems, 16(3), 342–362. doi: 10.7232/iems.2017.16.3.342
  • Fard, A. M. F., & Hajaghaei-Keshteli, M. (2018). A tri-level location-allocation model for forward/reverse supply chain. Applied Soft Computing, 62, 328–346. doi: 10.1016/j.asoc.2017.11.004
  • Fathollahi-Fard, A. M., & Hajiaghaei-Keshteli, M. (2018a). A bi-objective partial interdiction problem considering different defensive systems with capacity expansion of facilities under imminent attacks. Applied Soft Computing, 68, 343–359. doi: 10.1016/j.asoc.2018.04.011
  • Fathollahi-Fard, A. M., & Hajiaghaei-Keshteli, M. (2018b). A stochastic multi-objective model for a closed-loop supply chain with environmental considerations. Applied Soft Computing, 69, 232–249. doi: 10.1016/j.asoc.2018.04.055
  • Fathollahi-Fard, A. M., Hajiaghaei-Keshteli, M., & Mirjalili, S. (2019). A set of efficient heuristics for a home healthcare problem. Neural Computing and Applications, 1(21). doi: 10.1007/s00521-019-04126-8
  • Fathollahi-Fard, A. M., Hajiaghaei-Keshteli, M., & Mirjalili, S. (2018a). Hybrid optimizers to solve a tri-level programming model for a tire closed-loop supply chain network design problem. Applied Soft Computing, 70, 701–722. doi: 10.1016/j.asoc.2018.06.021
  • Fathollahi-Fard, A. M., Hajiaghaei-Keshteli, M., & Mirjalili, S. (2018b). Multi-objective Stochastic Closed-loop supply chain network design with Social Considerations. Applied Soft Computing, 71, 505–525. doi: 10.1016/j.asoc.2018.07.025
  • Fathollahi-Fard, A. M., Hajiaghaei-Keshteli, M., & Tavakkoli-Moghaddam, R. (2018a). A bi-objective green home health care routing problem. Journal of Cleaner Production, 200, 423–443. doi: 10.1016/j.jclepro.2018.07.258
  • Fathollahi-Fard, A. M., Hajighaei-Keshteli, M., & Tavakkoli-Moghaddam, R. (2018b). The social engineering optimizer (SEO). Engineering Applications of Artificial Intelligence, 72, 267–293. doi: 10.1016/j.engappai.2018.04.009
  • Fu, Y., Tian, G., Fathollahi-Fard, A. M., Ahmadi, A., & Zhang, C. (2019). 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, 226, 515–525. doi: 10.1016/j.jclepro.2019.04.046
  • Gharaei, A., & Jolai, F. (2018). A multi-agent approach to the integrated production scheduling and distribution problem in multi-factory supply chain. Applied Soft Computing, 188, 167–184.
  • Hajighaei-Keshteli, M., & Fathollahi Fard, A. M. (2018a). Sustainable closed-loop supply chain network design with discount supposition. Neural Computing and Applications, 1–35. doi: 10.1007/s00521-018-3369-5
  • Hajighaei-Keshteli, M., & Fathollahi-Fard, A. M. (2018b). A set of efficient heuristics and metaheuristics to solve the two-stage stochastic bi-level decision-making model for the distribution network problem. Computers & Industrial Engineering, 123, 378–395. doi: 10.1016/j.cie.2018.07.009
  • Hossain, M. S., & Hossain, M. M. (2018). Application of interactive fuzzy goal programming for multi-objective integrated production and distribution planning. International Journal of Process Management and Benchmarking, 8(1), 35–58. doi: 10.1504/IJPMB.2018.088656
  • Jamalnia, A., & Soukhakian, M. A. (2009). A hybrid fuzzy goal programming approach with different goal priorities to aggregate production planning. International Journal of Computers & Industrial Engineering, 56, 1474–1486. doi: 10.1016/j.cie.2008.09.010
  • Jolai, F., Razmi, J., & Rostami, N. K. M. (2011). A fuzzy goal programming and meta heuristic algorithms for solving integrated production: Distribution planning problem. Central European Journal of Operations Research, 19(4), 547–569. doi: 10.1007/s10100-010-0144-9
  • Kara, B. Y., & Tansel, B. C. (2000). On the single-assignment p-hub center problem. European Journal of Operational Research, 125(3), 648–655. doi: 10.1016/S0377-2217(99)00274-X
  • Kazemi, A., Zarandi, M. H. F., & Aziz mohammadi, M. (2017). A hybrid search approach in production-distribution planning problem in supply chain using multi-agent systems. International Journal of Operational Research, 28(4), 506–527. doi: 10.1504/IJOR.2017.082611
  • Kumar, R. S., Tiwari, M. K., & Goswami, A. (2014). Two-echelon fuzzy stochastic supply chain for the manufacturer-buyer integrated production-inventory system. International Journal of Intelligent, 122, 1024–1038.
  • Latpate, R. V., & Kurade, S. S. (2017). Fuzzy MOGA for supply chain models with Pareto decision space at different α-cuts. The International Journal of Advanced Manufacturing Technology, 91(9–12), 3861–3876. doi: 10.1007/s00170-016-9966-5
  • Lee, S., & Kim, D. (2014). An optimal policy for a single-vendor single buyer integrated production–distribution model with both deteriorating and defective items. International Journal of Production Economics, 147, 161–170. doi: 10.1016/j.ijpe.2013.09.011
  • LeMay, S., LeMay, S., Helms, M. M., Helms, M. M., Kimball, B., Kimball, B., … McMahon, D. (2017). Supply chain management: The elusive concept and definition. The International Journal of Logistics Management, 28(4), 1425–1453. doi: 10.1108/IJLM-10-2016-0232
  • Liu, S., & Papageorgiou, L. G. (2013). Multi-objective optimisation of production, distribution and capacity planning of global supply chains in the process industry. Omega, 41(2), 369–382. doi: 10.1016/j.omega.2012.03.007
  • Mahbub, N., Hasin, A. A., Aziz, R. A., & Sharin, A. (2017). Maximisation of total supply chain profit and minimisation of bullwhip effect in a multi-echelon supply chain network using particle swarm optimisation and genetic algorithm. International Journal of Integrated Supply Management, 11(2–3), 236–263. doi: 10.1504/IJISM.2017.086240
  • Mousavi, S. M., Bahreininejad, A., Musa, S. N., & Yusof, F. (2017). A modified particle swarm optimization for solving the integrated location and inventory control problems in a two-echelon supply chain network. Journal of Intelligent Manufacturing, 28(1), 191–206. doi: 10.1007/s10845-014-0970-z
  • Mousazadeh, M., Torabi, S. A., & Pishvaee, M. S. (2014). Green and reverse logistics management under fuzziness. In Supply chain management under fuzziness (pp. 607–637). Berlin: Springer.
  • Nazim, M., Hashim, M., Nadeem, A. H., Yao, L., & Ahmad, J. (2014). Multi objective production–distribution decision making model under fuzzy random environment. In Proceedings of the eighth international conference on management science and engineering management (pp. 591–601). Berlin: Springer.
  • Nemati, Y., & Alavidoost, M. H. (2018). A fuzzy bi-objective MILP approach to integrate sales, production, distribution and procurement planning in a FMCG supply chain. Soft Computing, 89, 1–20.
  • Nourifar, R., Mahdavi, I., Mahdavi-Amiri, N., & Paydar, M. M. (2017). Optimizing decentralized production–distribution planning problem in a multi-period supply chain network under uncertainty. Journal of Industrial Engineering International, 66, 1–16.
  • Rabbani, M., Zhalechian, M., & Farshbaf-Geranmayeh, A. (2016). A robust possibilistic programming approach to multiperiod hospital evacuation planning problem under uncertainty. International Transactions in Operational Research, 202, 566–582.
  • Rajkanth, R., Srinivasan, G., & Gopalakrishnan, M. (2017). Material flow optimisation in a multi-echelon and multi-product supply chain. International Journal of Logistics Systems and Management, 26(1), 105–124. doi: 10.1504/IJLSM.2017.080633
  • Sahebjamnia, N., Fathollahi-Fard, A. M., & Hajiaghaei-Keshteli, M. (2018). Sustainable tire closed-loop supply chain network design: Hybrid metaheuristic algorithms for large-scale networks. Journal of Cleaner Production, 196, 273–296. doi: 10.1016/j.jclepro.2018.05.245
  • Sakalli, U. S. (2017). Optimization of production-distribution problem in supply chain management under Stochastic and fuzzy uncertainties. Mathematical Problems in Engineering, 225, 167–179.
  • Samadi, A., Mehranfar, N., Fathollahi Fard, A. M., & Hajiaghaei-Keshteli, M. (2018). Heuristic-based metaheuristic to address a Sustainable supply chain network design problem. Journal of Industrial and Production Engineering, 35(2), 102–117. doi: 10.1080/21681015.2017.1422039
  • Storn, R., & Price, K. (1997). Differential evolution – a simple and efficient heuristic for global optimization over continuous spaces. Journal of Global Optimization, 11(4), 341–359. doi: 10.1023/A:1008202821328
  • Torabi, S. A., & Hassini, E. (2008). An interactive possibilistic programming approach for multiple objective supply chain master planning. Fuzzy Sets and Systems, 159(2), 193–214. doi: 10.1016/j.fss.2007.08.010
  • Wang, Y., Cai, Z., & Zhang, Q. (2012). Enhancing the search ability of differential evolution through orthogonal crossover. Information Sciences, 185(1), 153–177. doi: 10.1016/j.ins.2011.09.001
  • Wang, R. C., & Fang, H. H. (2001). Aggregate production planning with multiple objectives in a fuzzy environment. European Journal of Operational Research, 133, 521–536. doi: 10.1016/S0377-2217(00)00196-X
  • Xu, J., & Pei, W. (2013). Production-distribution planning of construction supply chain management under fuzzy random environment for large-scale construction projects. J Indus Manage Opt, 9, 31–56. doi: 10.3934/jimo.2013.9.31
  • Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8, 338–353. (Cited by: U.S. Sakalli, A note on fuzzy multi-objective production/distribution planning decisions with multi-product and multi-time period in a supply chain. International Journal of Computers and Industrial Engineering, 59, 1010–1012). doi: 10.1016/S0019-9958(65)90241-X
  • Zhalechian, M., Tavakkoli-Moghaddam, R., & Rahimi, Y. (2017). A self-adaptive evolutionary algorithm for a fuzzy multi-objective hub location problem: An integration of responsiveness and social responsibility. Engineering Applications of Artificial Intelligence, 62, 1–16. doi: 10.1016/j.engappai.2017.03.006
  • Zhalechian, M., Tavakkoli-Moghaddam, R., Zahiri, B., & Mohammadi, M. (2016). Sustainable design of a closed-loop location-routing-inventory supply chain network under mixed uncertainty. Transportation Research Part E: Logistics and Transportation Review, 89, 182–214. doi: 10.1016/j.tre.2016.02.011
  • Zitzler, E., & Thiele, L. (1998, September). Multiobjective optimization using evolutionary algorithms – a comparative case study. In International conference on parallel problem solving from nature (pp. 292–301). Berlin: Springer.

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