掉期(金融)
数学优化
动态规划
时间范围
计算机科学
电池(电)
启发式
采购
随机规划
流量网络
期限(时间)
运筹学
工程类
功率(物理)
经济
数学
运营管理
物理
财务
量子力学
作者
Frank Schneider,Ulrich W. Thonemann,Diego Klabjan
出处
期刊:Transportation Science
[Institute for Operations Research and the Management Sciences]
日期:2018-10-01
卷期号:52 (5): 1211-1234
被引量:55
标识
DOI:10.1287/trsc.2017.0781
摘要
An operator of a network of battery swap stations for electric vehicles must make a long-term investment decision on the number of batteries and charging bays in the system and periodic short-term decisions on when and how many batteries to recharge. Both decisions must be made concurrently, because there exists a trade-off between the long-term investment in batteries and charging bays, and short-term expenses for operating the system. Costs for electric energy as well as demand rates for batteries are stochastic: We consider an infinite time horizon for operation of the system. We derive an optimization problem, which cannot be solved optimally in a reasonable time for real world instances. By optimally solving various small problem instances, we show the mechanics of the model and the influence of its parameters on the optimal cost. We then develop a near-optimal solution heuristic based on Monte Carlo sampling following the ideas of approximate dynamic programming for the infinite horizon dynamic program. We show that operating battery swap stations in a network where lateral transshipments are allowed can substantially decrease expected operating costs. The online appendix is available at https://doi.org/10.1287/trsc.2017.0781
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