计算机应用 ›› 2015, Vol. 35 ›› Issue (7): 2096-2100.DOI: 10.11772/j.issn.1001-9081.2015.07.2096

• 行业与领域应用 • 上一篇    下一篇

基于多时间窗的油料保障模型

闫华1, 高黎1, 刘国勇2, 王红旗3   

  1. 1. 后勤工程学院 后勤信息与军事物流工程系, 重庆 401311;
    2. 62155部队, 河南 信阳 464132;
    3. 后勤工程学院 管理科学与工程系, 重庆 401311
  • 收稿日期:2015-01-20 修回日期:2015-03-22 出版日期:2015-07-10 发布日期:2015-07-17
  • 通讯作者: 闫华(1983-),男,甘肃临潭人,讲师,博士,主要研究方向:信息系统、系统优化建模与分析,yanhua_8304@163.com
  • 作者简介:高黎(1970-),男,北京人,副教授,博士,主要研究方向:信息系统、系统工程; 刘国勇(1970-),男,山西朔州人,工程师,主要研究方向:系统优化建模与分析。
  • 基金资助:

    后勤工程学院青年基金资助项目。

Petrol-oil and lubricants support model based on multiple time windows

YAN Hua1, GAO Li1, LIU Guoyong2, WANG Hongqi3   

  1. 1. Department of Logistical Information and Logistics Engineering, Logistic Engineering University, Chongqing 401311, China;
    2. Unit 62155, Xinyang Henan 464132, China;
    3. Department of Management Science and Engineering, Logistic Engineering University, Chongqing 401311, China
  • Received:2015-01-20 Revised:2015-03-22 Online:2015-07-10 Published:2015-07-17

摘要:

针对军用油料(POL)调拨运输优化问题,通过引入保障时间窗,考虑了油料保障过程中复杂的时间窗约束和运力约束,提出了基于多时间窗的油料调拨运输的约束满足问题(CSP)模型及其求解算法。首先,对油料保障点、油料需求点、保障时间窗、油料保障需求及油料保障任务等要素进行了形式化描述;在此基础上,建立了油料保障CSP模型,并采用理想点法,将模型中的多目标转化为单目标规划问题;设计了基于粒子群优化(PSO)算法的模型求解方法和步骤,并通过算例介绍了模型的具体运用。算例中,将利用所提模型求解得到的优化方案与最大化油料保障量为单一目标的模型优化方案进行比较,两种方案下的运力安排已达最大,但对各油料需求保障时间的安排,所提模型求解方案中每个油料需求的开始保障时间都不晚于单目标模型求解方案中的保障时间。通过对不同优化方案的比较,表明所提模型和算法能够有效解决多目标油料保障优化问题。

关键词: 多时间窗, 油料保障, 约束满足问题, 优化模型, 粒子群算法

Abstract:

In this paper, the military Petrol-Oil and Lubricants (POL) allotment and transportation problem was studied by introducing the concept of support time window. Considering the complicated restrictions of POL support time and transportation capability, the POL allotment and transportation model based on multiple time windows was proposed by using Constraint Satisfaction Problem (CSP) modelling approach. Firstly, the formalized description of the problem elements was presented, such as POL support station, demand unit, support time window, support demand, and support task. Based on the formalized description, the CSP model for POL support was constructed. The multi-objective model was transformed into single-objective one by using perfect point method. Finally, the solving procedure and its steps were designed based on Particle Swarm Optimization (PSO) algorithm, and an arithmetic example was followed to demonstrate the application of the method. In the example, the two optimization schemes obtained by the model given in this paper and got by the model in which the objective is maximizing the quantity supported were compared. In the two schemes, the transportation capacity both reached a maximum utilization, but the start supporting time of each POL demand in the scheme of the proposed method was no later than the one in the scheme of the single-objective model. By comparing different optimization schemes, it is shown that the proposed model and algorithm can effectively solve the multi-objective POL support optimization problem.

Key words: multiple time windows, Petrol-Oil and Lubricants (POL) support, constraint satisfaction problem, optimization model, Particle Swarm Optimization (PSO) algorithm

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