-
摘要: 考虑重点方向或区域中, 各重要隘口、通道、敏感地带等突发事件之间的关联性(连锁反应的可能性) 和需求的随机性, 在多个预置储备仓库构成储备网络和多个需求点组成需求网络的条件下, 研究了用储备网络保障需求网络的预置储备规模和储备分布优化问题, 分析了需求网络在各点突发事件和需求随机下总需求的分布特征; 在保证预置储备规模有效性、经济性与储备分布合理性的基础上, 建立了给定安全保障概率下的储备规模模型和过程响应准则下的分布式储备模型(统称储备模型); 根据模型特征将分布式储备模型分解为双层模型, 对随机需求采用样本化处理, 并在此基础上建立了针对性的遗传-模拟退火算法求解双层模型; 基于变异系数的概念, 提出了针对突发事件和需求随机的储备方案稳健性指标, 对储备模型及其算法进行了稳健性分析, 并通过案例应用验证了储备模型及其算法的有效性。研究结果表明: 相较于就近分区准则, 储备规模模型及其算法能在确保安全保障概率的前提下将储备规模降低约1/3;相较于极大极小化准则, 过程响应准则下的分布式储备方案可使首批物资响应时间减少11%, 使90%物资的响应时间减少21%;在面临需求网络中突发事件和需求的随机性波动时, 储备方案的波动幅度不超过需求波动的80%, 体现了较好的稳健性。Abstract: Considering the correlations of emergencies (possibility of chain reaction) among the important pass, passageway, and sensitive zone, and the randomness of demands in the key directions or areas, the optimization problems of preset reserve scale and reserve distribution about the reserve network supporting the demand network were studied. The reserve network consisted of multiple preset reserve warehouses, and the service demand network consisted of multiple stochastic demand points. The distribution characteristics of the total demand in the demand network were analyzed under the conditions that the emergency at each point and the demand quantity were random. Ensuring the effectiveness and economy of the preset reserve scale and the rationality of the reserve distribution, the reserve scale model under the given securityprobability and the distributed reserve model under the process response criterion (collectively called reserve model) were established. According to the characteristics of the model, the distributed reserve model was decomposed into a bi-level model. The sample processing method was used to resolve the random demand problem. On this basis, agenetic-simulated annealing algorithm was constructed to solve this model. Based on the concept of variation coefficient, a robustness index for reserve scheme with random emergency and random demand was proposed to analyze the robustness of the reserve model and its algorithm. The validities of the reserve model and its algorithm were verified by a case application. Research result shows that in comparison with the nearby partition principle, the reserve scale model and its algorithm can reduce the reserve scale by approximately 1/3 under the premise of ensuring the security probability. In comparison with the maximin criterion, the distributed reserve scheme under the process response criterion can reduce the response time of the first batch of materials by 11%, and the response time of 90% of materials reduces by 21%. When facing the stochastic fluctuation of emergency and demand in the demand network, the amplitude of fluctuation for the distributed reserve scheme is no more than 80% of the demand fluctuation, which suggests better robustness.
-
图 2 极大极小化准则下最大响应时间分布
Figure 2. Distribution of maximum response time under maximin criterion
表 3 某重点区域总需求与突发事件的概率分布
Table 3. Probability distributions of total demand and emergency in a key area
下载: 导出CSV
表 4 就近分区策略下储备仓库的保障对象与储备规模
Table 4. Support objects and reserve scales of reserve warehouses under nearby partition principle
下载: 导出CSV
-
[1] 刘俊, 封少娟. 美军境外行动物资预置保障对我军的启示[J]. 物流工程与管理, 2015, 37 (9): 124-126. doi: 10.3969/j.issn.1674-4993.2015.09.047LIU Jun, FENG Shao-juan. Enlightenment on the U. S. military preposition stock practice[J]. Logistics Engineering and Management, 2015, 37 (9): 124-126. (in Chinese). doi: 10.3969/j.issn.1674-4993.2015.09.047 [2] 赵振华, 姜大立. 美军战备物资储备的主要做法[J]. 物流技术, 2015, 34 (13): 299-300. https://www.cnki.com.cn/Article/CJFDTOTAL-WLJS201513096.htmZHAO Zhen-hua, JIANG Da-li. Major practices of American army in war reserve management[J]. Logistics Technology, 2015, 34 (13): 299-300. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-WLJS201513096.htm [3] 徐东. 建立物资预置体系势在必行[J]. 仓储管理与技术, 1998 (3): 8-10.XU Dong. Necessity of establishing preset reserve system[J]. Storage Management and Technology, 1998 (3): 8-10. (in Chinese). [4] 任岚燕. 我军战场预置储备中的军事经济效益浅析[J]. 军事经济研究, 2000 (9): 51-53. https://www.cnki.com.cn/Article/CJFDTOTAL-JSYP200009017.htmREN Lan-yan. Briefly on the military economic benefit of battlefield reserve[J]. Military Economic Research, 2000 (9): 51-53. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-JSYP200009017.htm [5] 杜伟, 邓武林. 加强西北边境地区军交运输器材预置储备探析[J]. 汽车运用, 2015 (6): 13-14.DU Wei, DENG Wu-lin. Research on pre-reservation of military transportation equipment in northwest frontier area[J]. Automobile Application, 2015 (6): 13-14. (in Chinese). [6] 赵达, 李军, 李妍峰, 等. 随机需求库存-路径问题: 研究现状及展望[J]. 系统工程, 2007, 25 (8): 38-44. https://www.cnki.com.cn/Article/CJFDTOTAL-GCXT200708008.htmZHAO Da, LI Jun, LI Yan-feng, et al. Inventory routing problem with stochastic demand research status and prospect[J]. Systems Engineering, 2007, 25 (8): 38-44. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-GCXT200708008.htm [7] 赵达, 李军, 马丹祥, 等. 固定分区下随机需求IRP问题最优策略及算法[J]. 管理科学学报, 2016, 19 (12): 25-35. https://www.cnki.com.cn/Article/CJFDTOTAL-JCYJ201612003.htmZHAO Da, LI Jun, MA Dan-xiang, et al. Optimal strategy and algorithm of stochastic demand inventory routing problem under fixed partition policy[J]. Journal of Management Sciences, 2016, 19 (12): 25-35. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-JCYJ201612003.htm [8] HUMAIR S, WILLEMS S P. Optimizing strategic safety stock placement in general acyclic networks[J]. Operations Research, 2011, 59 (3): 781-787. doi: 10.1287/opre.1100.0913 [9] HUMAIR S, RUARK D, WILLEMS S P, et al. Incorporating stochastic lead times into the guaranteed service model of safety stock optimization[J]. Interfaces, 2013, 43 (5): 421-434. doi: 10.1287/inte.2013.0699 [10] CHOPRA S, REINHARDT G, DADA M. The effect of lead time uncertainty on safety stocks[J]. Decision Sciences, 2004, 35 (1): 1-24. doi: 10.1111/j.1540-5414.2004.02332.x [11] ALBEY E, YANIKO (GLU I·, UZSOY R. Load dependent lead time modelling: a robust optimization approach[C]∥CHAN W K V, D'AMBROGIO A, ZACHAREWICZ G, et al. Proceedings of the 2017Winter Simulation Conference. New York: IEEE, 2017: 3531-3542. [12] HSU S L, HUANG Y F. An integrated inventory model with controllable lead time and distribution-free demand[J]. Applied Stochastic Models in Business and Industry, 2010, 26 (4): 416-430. [13] LI Hai-tao, JIANG Da-li. New model and heuristics for safety stock placement in general acyclic supply chain networks[J]. Computers and Operations Research, 2012, 39 (7): 1333-1344. [14] MAGNANTI T L, SHEN Z J M, SHU J, et al. Inventory placement in acyclic supply chain networks[J]. Operation Research Letters, 2006, 34 (2): 228-238. [15] HVATTUM L M, L∅KKETANGEN A, LAPORTE G. Scenario tree-based heuristics for stochastic inventory-routing problems[J]. Informs Journal on Computing, 2009, 21 (2): 268-285. [16] YADOLLAHI E, AGHEZZAF E, RAA B. Managing inventory and service levels in a safety stock-based inventory routing system with stochastic retailer demands[J]. Applied Stochastic Models in Business and Industry, 2017, 33: 369-381. [17] JUAN A A, GRASMAN S E, CACERES-CRUZ J, et al. A simheuristic algorithm for the single-period stochastic inventory-routing problem with stock-outs[J]. Simulation Modelling Practice and Theory, 2014, 46 (4): 40-52. [18] RAHIM M K I A, ZHONG Y, AGHEZZAF E H, et al. Modelling and solving the multiperiod inventory-routing problem with stochastic stationary demand rates[J]. International Journal of Production Research, 2014, 52 (14): 4351-4363. [19] 阮旻智, 刘任洋. 随机需求下多层级备件的横向转运配置优化模型[J]. 系统工程理论与实践, 2016, 36 (10): 2689-2698. https://www.cnki.com.cn/Article/CJFDTOTAL-XTLL201610023.htmRUAN Min-zhi, LIU Ren-yang. Configuration and optimization model for multi-indenture spares with lateral transshipments under stochastic demand[J]. Systems Engineering—Theory and Practice, 2016, 36 (10): 2689-2698. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-XTLL201610023.htm [20] 姜燕宁, 郝书池. 基于部分跨级和集中存储模式的库存配置与选址决策模型[J]. 公路交通科技, 2016, 33 (11): 152-158. https://www.cnki.com.cn/Article/CJFDTOTAL-GLJK201611023.htmJIANG Yan-ning, HAO Shu-chi. Inventory allocation and location decision model based on partial cross-level and centralized storage[J]. Journal of Highway and Transportation Research and Development, 2016, 33 (11): 152-158. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-GLJK201611023.htm [21] 杨志林, 李擎卿, 林冠男. 随机需求下单供应商与多零售商的生产-库存-运输联合优化模型[J]. 大学数学, 2015, 31 (5): 12-19. https://www.cnki.com.cn/Article/CJFDTOTAL-GKSX201505003.htmYANG Zhi-lin, LI Qing-qing, LIN Guan-nan. Integrated production-inventory-transportation optimization model under stochastic demand with single-vendor and multi-retailer[J]. College Mathematics, 2015, 31 (5): 12-19. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-GKSX201505003.htm [22] 王宪杰, 黄佳伟, 王淑云. 基于安全库存系数的一体化冷链库存价格协调[J]. 工业工程与管理, 2016, 21 (4): 43-49. https://www.cnki.com.cn/Article/CJFDTOTAL-GYGC201604007.htmWANG Xian-jie, HUANG Jia-wei, WANG Shu-yun. Price coordination for integration of cold chain inventory[J]. Industrial Engineering and Management, 2016, 21 (4): 43-49. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-GYGC201604007.htm [23] 全春光, 刘志学, 邹安全, 等. 随机需求下单供应商两分销商VMI协调策略[J]. 系统工程理论与实践, 2013, 33 (7): 1801-1812. https://www.cnki.com.cn/Article/CJFDTOTAL-XTLL201307024.htmQUAN Chun-guang, LIU Zhi-xue, ZOU An-quan, et al. Coordination policy of VMI with one supplier and two distributors under stochastic demand[J]. Systems Engineering—Theory and Practice, 2013, 33 (7): 1801-1812. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-XTLL201307024.htm [24] 周荷芳, 李宗平, 杜文. 多级库存系统中安全库存与配送结构的关系分析[J]. 西南交通大学学报, 2001, 36 (5): 457-461. https://www.cnki.com.cn/Article/CJFDTOTAL-XNJT200105001.htmZHOU He-fang, LI Zong-ping, DU Wen. On the connection between optimal stock level and distribution structure in multi-echelon storage system[J]. Journal of Southwest Jiaotong University, 2001, 36 (5): 457-461. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-XNJT200105001.htm [25] MONCAYO-MARTÍNEZ L A, RESÉNDIZ-FLORES E O, MERCADO D, et al. Placing safety stock in logistic networks under guaranteed-service time inventory models: an application to the automotive industry[J]. Journal of Applied Research and Technology, 2014, 12 (3): 538-550. [26] 汪定伟, 张国祥. 突发性灾害救援中心选址优化的模型与算法[J]. 东北大学学报: 自然科学版, 2005, 26 (10): 953-956. https://www.cnki.com.cn/Article/CJFDTOTAL-DBDX200510009.htmWANG Ding-wei, ZHANG Guo-xiang. Model and algorithm to optimize location of catastrophic rescue center[J]. Journal of Northeastern University: Natural Science, 2005, 26 (10): 953-956. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-DBDX200510009.htm -
点击查看大图
图(8) / 表(5)
计量
- 文章访问数: 635
- HTML全文浏览量: 120
- PDF下载量: 506
- 被引次数: 0
