考虑资源约束和数量折扣的联合补货-选址库存协同优化研究
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摘要
本文构建了一种基于联合补货策略的配送中心选址-库存协同优化新模型,该模型允许缺货,有资源约束且考虑数量折扣;同时设计了一种融合模拟退火思想的双种群独立进化的自适应差分算法(Adaptive Simulated Annealing Differential Algorithm,ASADE)对该模型进行求解,并通过算例与自适应差分算法、改进的蛙跳算法进行对比,证实了ASADE算法的有效性。最后进行了敏感性分析,讨论相关参数变动对总成本的影响,可为管理者更好决策提供有益的依据。
A new joint replenishment-location inventory model( JR-LIP) is proposed considering resource constraints and quantity discount,which permits shortage. An adaptive differential evolution algorithm based on simulated annealing with binary population independent evolution is redesigned to solve the proposed JR-LIP model. Compared with the adaptive differential algorithm( AHDE) and the improved frog leaping algorithm( FLA),the numerical studies show the effectiveness of the proposed ASADE. Finally,the sensitivity analysis is further conducted to discuss the influence of parameters on the total cost,which can provide useful references for managers to make better decisions.
A new joint replenishment-location inventory model( JR-LIP) is proposed considering resource constraints and quantity discount,which permits shortage. An adaptive differential evolution algorithm based on simulated annealing with binary population independent evolution is redesigned to solve the proposed JR-LIP model. Compared with the adaptive differential algorithm( AHDE) and the improved frog leaping algorithm( FLA),the numerical studies show the effectiveness of the proposed ASADE. Finally,the sensitivity analysis is further conducted to discuss the influence of parameters on the total cost,which can provide useful references for managers to make better decisions.
引文
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[15] Guo H X,Li Y N,Li J L,Sun H,Wang D Y.Differential evolution improved with self-adaptive control parameters based on simulated annealing[J]. Swarm and Evolutionary Computation,2014,19:52-67.
[16]王林,顿彩霞,张金隆.基于混合差分进化算法的联合补货-配送优化模型[J].中国管理科学,2012,20(3):86-93.
[17] Gao L,Zhou Y Z,Li X Y,Pan Q K,Yi W C. Multiobjective optimization based reverse strategy with differential evolution algorithm for constrained optimization problems[J]. Expert Systems with Applications,2015,42(14):5976-5987.
[18] Tirronen V,Neri F. Differential evolution with fitness diversity self-adaptation[A]. in Chiong R.(eds)NatureInspired Algorithms for Optimisation. Studies in Computational Intelligence[C]Springer,Berlin,Heidelberg,2009,193:199-234.
[19] Zhang J Q,Sanderson A C. JADE:adaptive differential evolution with optional external archive[J]. IEEE Transactions on Evolutionary computation,2009, 13(5):945-958.
[20]李亚楠,郭海湘,黎金玲,刘晓.一种基于模拟退火的参数自适应差分演化算法及其应用[J].系统管理学报,2016,25(4):652-662.
[21]刘琼,许金辉,张超勇.基于改进蛙跳算法的鲁棒性车间布局[J].计算机集成制造系统,2014,20(8):1879-1886.
[2] Cha B C,Moon I K,Park J H. The joint replenishment and delivery scheduling of the one-warehouse,n-retailer system[J]. Transportation Research Part E-logistics and Transportation,2008,44(5):720-730.
[3] Silva F,Gao L. A joint replenishment inventory-location model[J]. Networks and Spatial Economics,2013,13(1):107-122.
[4] Wang L,Qu H,Chen T,Yan F P. An effective hybrid self-adapting differential evolution algorithm for the joint replenishment and location-inventory problem in a threelevel supply chain[J]. Scientific World Journal,2013,Article ID 270249,1-11. doi:10. 1155/2013/270249.
[5] Qu H,Wang L,Liu R. A contrastive study of the stochastic location-inventory problem with joint replenishment and independent replenishment[J]. Expert Systems with Applications,2015,42(4):2061-2072.
[6] Pirkul H,Aras O A. Capacitated multiple items ordering problem with quantity discounts[J]. IIE Transactions,1985,17(3):206-211.
[7] Moon I K,Goyal S K,Cha B C. The joint replenishment problem involving multiple suppliers offering quantity discounts[J]. International Journal of Systems Science,2008,39(6):629-637.
[8] Cui L G,Deng J,Wang L,Xu M Z,Zhang Y J. A novel locust swarm algorithm for the joint replenishment problem considering multiple discounts simultaneously[J]. Knowledge-Based Systems,2016,111:51-62.
[9] Esther A,Dev J,Robin R. Computational complexity of uncapacitated multi-echelon production planning problems[J]. Operations Research Letters,1989,8(2):61-66.
[10] Amaya C A, Carvajal J, Castano F. A heuristic framework based on linear programming to solve the constrained joint replenishment problem(C-JRP)[J].International Journal of Production Economics,2013,144(1):243-247.
[11] Chen Y,Wahab M I M,Ongkunaru P. A joint replenishment problem considering multiple trucks with shipment and resource constraints[J]. Computers&Operations Research,2016,74:53-63.
[12] Ongkunaruk P,Wahab M I M,Chen Y. A genetic algorithm for a joint replenishment problem with resource and shipment constraints and defective items[J]. International Journal of Production Economics,2016,175:142-152.
[13] Wang L, He J, Wu D S, Zeng Y R. A novel differential evolution algorithm for joint replenishment problem under interdependence and its application[J].International Journal of Production Economics,2012,135(1):190-198.
[14] Qu H,Wang L,Zeng Y R. Modeling and optimization for the joint replenishment and delivery problem with heterogeneous items[J]. Knowledge-Based Systems,2013,54:207-215.
[15] Guo H X,Li Y N,Li J L,Sun H,Wang D Y.Differential evolution improved with self-adaptive control parameters based on simulated annealing[J]. Swarm and Evolutionary Computation,2014,19:52-67.
[16]王林,顿彩霞,张金隆.基于混合差分进化算法的联合补货-配送优化模型[J].中国管理科学,2012,20(3):86-93.
[17] Gao L,Zhou Y Z,Li X Y,Pan Q K,Yi W C. Multiobjective optimization based reverse strategy with differential evolution algorithm for constrained optimization problems[J]. Expert Systems with Applications,2015,42(14):5976-5987.
[18] Tirronen V,Neri F. Differential evolution with fitness diversity self-adaptation[A]. in Chiong R.(eds)NatureInspired Algorithms for Optimisation. Studies in Computational Intelligence[C]Springer,Berlin,Heidelberg,2009,193:199-234.
[19] Zhang J Q,Sanderson A C. JADE:adaptive differential evolution with optional external archive[J]. IEEE Transactions on Evolutionary computation,2009, 13(5):945-958.
[20]李亚楠,郭海湘,黎金玲,刘晓.一种基于模拟退火的参数自适应差分演化算法及其应用[J].系统管理学报,2016,25(4):652-662.
[21]刘琼,许金辉,张超勇.基于改进蛙跳算法的鲁棒性车间布局[J].计算机集成制造系统,2014,20(8):1879-1886.