基于PIWOA的绿色闭环供应链网络多目标模糊优化设计

doi:10.3969/j.issn.1007-7375.2021.04.004

摘要/Abstract

摘要： 针对闭环供应链网络优化设计问题，建立了一种基于Me测度的闭环供应链网络多目标优化设计模型，以此降低供应链网络设计中不确定性因素在求解时的影响。首先，针对多层级闭环供应链网络，建立以成本最小、CO₂排放量最小以及社会效益最大为目标的优化函数，并采用Me测度和三角模糊数对模型及相关约束进行模糊处理，得到不确定性闭环供应链网络优化模型；其次，在原有鲸鱼算法的基础上，引入变异收敛因子，增强其搜索能力，并将Pareto引入改进后的鲸鱼算法求解所建模型；最后，通过数值实例和仿真分析验证算法在搜索能力、时间以及优化目标函数值等方面具有较强的优势和性能。

关键词: 闭环供应链网络设计, 模糊优化, 三角模糊数, 鲸鱼算法, 不确定性模型

Abstract: Aiming at the optimization design of closed-loop supply chain network, a multi-objective optimization design model of closed-loop supply chain network based on Me measure is established to reduce the influence of uncertainty factors in the solution of supply chain network design. Firstly, based on the multi-level closed-loop supply chain network, an optimization function with minimum cost, minimum CO₂ emission and maximum social benefit is established. The Me measure and triangular fuzzy number are used to conduct fuzzy processing of the model and related constraints, and the uncertain closed-loop supply chain network optimization model obtained. Secondly, on the basis of the original whale algorithm, variable convergence factor is introduced to enhance its search ability, and Pareto introduced into the improved whale algorithm to solve the established model. Finally, numerical examples and simulation analysis verify that the algorithm has strong advantages and performance in search capability, time and optimization objective function value.

Key words: design of closed-loop supply chain network, fuzzy optimization, triangular fuzzy number, whale algorithm, uncertainty model

中图分类号:

F253
F272

董海, 吴瑶. 基于PIWOA的绿色闭环供应链网络多目标模糊优化设计[J]. 工业工程, 2021, 24(4): 27-35.

DONG Hai, WU Yao. Green Closed-loop Supply Chain Network Based on PIWOA Multi-objective Fuzzy Optimal Design[J]. Industrial Engineering Journal, 2021, 24(4): 27-35.

参考文献

[1] LISTES O, DEKKER R. A stochastic approach to a case study for product recovery network design[J]. European Journal of Operational Research, 2005, 160(1): 268-287
[2] PATI R K, VRAT P, KUMAR P. A goal programming model for paper recycling system[J]. Special Issue on Multiple Criteria Decision Making for Engineering, 2008, 36(3): 405-417
[3] DEHGHANIAN F, MANSOUR S. Designing sustainable recovery network of end-of-life products using genetic algorithm[J]. Resource Conserve Recycle, 2009, 53(10): 559-570
[4] DEVIKA K, JAFARIAN A, NOURBAKHSH V. Designing a sustainable closed-loop supply chain network based on triple bottom line approach: a comparison of metaheuristics hybridization techniques[J]. European Journal of Operation Research, 2014, 235(3): 594-615
[5] CHEN Y W, WANG L C, WANG A, et al. A particle swarm approach for optimizing a multi-stage closed loop supply chain for the solar cell industry[J]. Robotics and Computer-Integrated Manufacturing, 2017, 43: 111-123
[6] SAHEBJAMMIA N, FARD A M F, HAJIAGHAEI-KESHTELI M. Sustainable tire closed-loop supply chain network design: hybrid metaheuristic algorithms for large-scale networks[J]. Journal Cleaner Production, 2018, 196: 273-296
[7] 吕宝龙, 张桂涛, 刘阳, 等. 考虑碳税和产品绿色度的闭环供应链网络Nash博弈均衡模型[J]. 中国人口·资源与环境, 2019, 29(1): 59-69
LYU Baolong, ZHANG Guitao, LIU Yang, et al. Nash game equilibrium model of closed-loop supply chain network considering carbon tax and product greenness[J]. China Population Resources and Environment, 2019, 29(1): 59-69
[8] OZCEYLAN E, PAKSOY T. Fuzzy multi-objective linear programming approach for optimizing a closed-loop supply chain network[J]. International Journal of Production Research, 2013, 51(8): 2443-2461
[9] OZKIR V, BASHGIL H. Multi-objective optimization of closed-loop supply chains in uncertain environment[J]. Journal Cleaner Production, 2013, 41: 114-125
[10] OZCEYLAN E, PAKSOY T. Interactive fuzzy programming approaches to the strategic and tactical planning of a closed-loop supply chain under uncertainty[J]. International Journal of Production Research, 2014, 52(8): 2363-2387
[11] TSAO Y C, THANH V V, LU J C, et al. Designing sustainable supply chain networks under uncertain environments: fuzzy multi-objective programming[J]. Journal Cleaner Production, 2018, 174: 1550-1565
[12] FAKHRZAD M B, 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[J]. RAIRO Operation Research, 2019, 53(3): 963-990
[13] PISHVAEE M, KIANFAR K, KARIMI B. Reverse logistics network design using simulated annealing[J]. The International Journal of Advanced Manufacturing Technology, 2010, 47(1): 269-281
[14] WANG H F, HSU H W. A closed-loop logistic model with a spanning-tree based genetic algorithm[J]. Computer Operation Research, 2010, 37(2): 376-389
[15] FAKHRZAD M B, TALEBZADEH P, GOODARZIAN F. Mathematical formulation and solving of green closed-loop supply chain planning problem with production, distribution and transportation reliability[J]. International Journal Engineering, 2018, 31(12): 2059-2067
[16] MIRJALILI Seyedali, LEWIS Andrew. The whale optimization algorithm[J]. Advances in Engineering Software, 2016, 95: 51-67
[17] XU J, ZHPU X. Approximation based fuzzy multi-objective models with expected objectives and chance constraints: Application to earth-rock work allocation[J]. Information Sciences, 2013, 238(7): 75-95
[18] WANG Z X, LIU Y J, FAN Z P. Ranking LR fuzzy number based on deviation degree[J]. Information Sciences., 2009, 179(13): 2070-2077
[19] 龙文, 蔡绍洪, 焦建军,等. 求解大规模优化问题的改进鲸鱼优化算法[J]. 系统工程理论与实践, 2017, 37(11): 2984-2994
LONG Wen, CAI Shaohong, JIAO Jianjun, et al. Improved whale optimization algorithm for large scale optimization problems[J]. Systems Engineering Theory and Practice, 2017, 37(11): 2984-2994