水准点(测量)
极限(数学)
数学优化
计算机科学
线性化
非线性系统
燃料效率
布线(电子设计自动化)
车辆路径问题
控制理论(社会学)
数学
控制(管理)
工程类
汽车工程
数学分析
物理
人工智能
量子力学
计算机网络
地理
大地测量学
作者
Yiyong Xiao,Xiaorong Zuo,Jiaoying Huang,Abdullah Konak,Yuchun Xu
标识
DOI:10.1016/j.amc.2020.125072
摘要
In this paper, we presented an ε-accurate approach to conduct a continuous optimization on the pollution routing problem (PRP). First, we developed an ε-accurate inner polyhedral approximation method for the nonlinear relation between the travel time and travel speed. The approximation error was controlled within the limit of a given parameter ε, which could be as low as 0.01% in our experiments. Second, we developed two ε-accurate methods for the nonlinear fuel consumption rate (FCR) function of a fossil fuel-powered vehicle while ensuring the approximation error to be within the same parameter ε. Based on these linearization methods, we proposed an ε-accurate mathematical linear programming model for the continuous PRP (ε-CPRP for short), in which decision variables such as driving speeds, travel times, arrival/departure/waiting times, vehicle loads, and FCRs were all optimized concurrently on their continuous domains. A theoretical analysis is provided to confirm that the solutions of ε-CPRP are feasible and controlled within the predefined limit. The proposed ε-CPRP model is rigorously tested on well-known benchmark PRP instances in the literature, and has solved PRP instances optimally with up to 25 customers within reasonable CPU times. New optimal solutions of many PRP instances were reported for the first time in the experiments.
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