Simulation and Evaluation of Network Simplex Algorithm and its Extensions for Vehicle Scheduling Problems in Ports

H. Rashidi
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引用次数: 4

Abstract

Article History: Received: 10 Oct. 2018 Accepted: 24 Feb. 2019 The Minimum Cost Flow (MCF) problem is a well-known problem in the area of network optimization. To tackle this problem, Network Simplex Algorithm (NSA) is the fastest solution method. NSA has three extensions, namely Network Simplex plus Algorithm (NSA), Dynamic Network Simplex Algorithm (DNSA) and Dynamic Network Simplex plus Algorithm (DNSA). The objectives of the research reported in this paper are to simulate and investigate the advantages and disadvantages of NSA compared with those of the three extensions in practical situations. To perform the evaluation, an application of these algorithms to scheduling problem of automated guided vehicles in container terminal is used. In the experiments, the number of iterations, CPU-time required to solve problems, overheads and complexity are considered.
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港口车辆调度问题的网络单纯形算法及其扩展仿真与评价
文章历史:接收时间:2018年10月10日接受时间:2019年2月24日最小成本流(MCF)问题是网络优化领域的一个众所周知的问题。为了解决这个问题,网络单纯形算法(NSA)是最快的解决方法。NSA有三个扩展,分别是网络单纯形加算法(NSA)、动态网络单纯形算法(DNSA)和动态网络单纯形加算法(DNSA)。本文报道的研究目的是在实际情况下模拟和研究NSA与三种扩展相比的优缺点。为了进行评估,将这些算法应用于集装箱码头自动化引导车辆的调度问题。在实验中,考虑了迭代次数、解决问题所需的CPU时间、开销和复杂性。
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