A Improved Subgradient Lagrangian Relaxation Algorithm for Solving the Stochastic Demand Inventory Routing Problem

Q2 Engineering Cyber-Physical Systems Pub Date : 2021-07-27 DOI:10.1080/23335777.2021.1946719
Yuan-Yuan Zhao, Qian-qian Duan
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引用次数: 0

Abstract

ABSTRACT In order to improve the coordination efficiency of vehicle routing problem, a multi-level stochastic demand in ventory routing problem was established in this paper, which minimizes the total cost of the system by determining the relation among inventory of distribution center, fleets, and customer needs. Solving the Lagrangian dual problem by the traditional subgradient Lagrangian relaxation algorithm may easily cause oscillation and then slow down the solving speed. To tackle the problem, an improved subgradient Lagrangian relaxation algorithm was proposed. Compared with the traditional subgradient algorithm , the proposed method is faster and improves the quality of the approximate solution.
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求解随机需求库存路径问题的改进亚梯度拉格朗日松弛算法
摘要为了提高车辆路径问题的协调效率,通过确定配送中心、车队和客户需求之间的库存关系,建立了多层次随机需求库存路径问题,使系统总成本最小化。传统的次梯度拉格朗日松弛算法求解拉格朗日对偶问题时,容易引起振荡,从而降低求解速度。为了解决这一问题,提出了一种改进的次梯度拉格朗日松弛算法。与传统的次梯度算法相比,该方法速度更快,提高了近似解的质量。
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来源期刊
Cyber-Physical Systems
Cyber-Physical Systems Engineering-Computational Mechanics
CiteScore
3.10
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