数学优化
车辆路径问题
增广拉格朗日法
计算机科学
拉格朗日松弛
放松(心理学)
块(置换群论)
节点(物理)
流量网络
离散化
布线(电子设计自动化)
状态空间
数学
工程类
计算机网络
社会心理学
数学分析
统计
几何学
结构工程
心理学
作者
Senyan Yang,Lianju Ning,Pan Shang,Lu Tong
标识
DOI:10.1016/j.tre.2020.101891
摘要
This paper studies the vehicle routing problem with mixed backhauls and time windows (VRPMBTW) for city logistics. A time-discretized multi-commodity network flow optimization model is proposed in an extended state-space-time network representation, where the time-dependent pickups and deliveries can be depicted by extending the state dimensions. By implementing an augmented Lagrangian relaxation technique, the VRPMBTW is reformulated as a quadratic 0–1 programming model, which is further decomposed into the standard least-cost-path sub-problems, and iteratively solved by dynamic programming in a block nonlinear Gauss-Seidel framework. The proposed approach is tested on the simple 9-node network and the real-world Chicago sketch network.
科研通智能强力驱动
Strongly Powered by AbleSci AI