LRP Model and Algorithm of Expressway Logistics Network Planning Based on Internet of Things

Author:

Kou Zheng1ORCID,Zhang Man2ORCID

Affiliation:

1. College of Business, Yancheng Teachers University, Yancheng 224007, Jiangsu, China

2. Economic and Trade Department, Yancheng Polytechnic College, Yancheng 224005, Jiangsu, China

Abstract

With the continuous improvement of the expressway logistics network, the location-routing problems (LRP) have become the obstacle to be overcome in the development of related industries. Based on the needs of modernization, in the era of the Internet of Things, classic traffic path planning algorithms can no longer meet the increasingly diverse needs, and related research results are not ideal. To reduce logistics costs and meet customer needs, this paper studies transportation route planning models and algorithms based on Internet of Things technology and particle swarm optimization. Firstly, the LRP model of expressway logistics network planning analyzes the achievement of goals, lists the assumptions, and builds the LRP model of expressway logistics network planning based on the mathematical model of path planning. Then the model is optimized and solved based on the particle swarm optimization algorithm. In order to verify the effectiveness and feasibility of the algorithm, MATLAB is used to simulate the algorithm. Finally, the LRP particle swarm optimization model of highway logistics network planning is put into the actual distribution work of a logistics company to analyze the change of distribution cost and investigate the related satisfaction. Experimental data show that the improved particle swarm optimization algorithm in this paper begins to converge in the 100th generation, the shortest running time is 57s, and the value of the objective function fluctuates slightly around 880. This shows that the model algorithm in this paper has strong search ability and stability. In the simulation experiment, the optimal objective function value of the model is 1001 yuan, which can be used to formulate the optimal distribution scheme. In the actual distribution work, the total cost of distribution before and after the application of the model was 12176.99 yuan and 9978.4 yuan, the fuel consumption cost decreased by 2097.23 yuan, and the penalty cost decreased by 85%. In the satisfaction survey, the satisfaction of all people was 9 points or above, with an average score of 9.42 points. This shows that the LRP particle swarm optimization model of expressway logistics network planning based on the Internet of Things technology can effectively save distribution costs and improve satisfaction.

Publisher

Hindawi Limited

Subject

Computer Networks and Communications,Computer Science Applications

Reference26 articles.

1. Major requirements for building smart homes in smart cities based on internet of things technologies;T. K. L. Hui;Future Generation Computer Systems,2016

2. Routing problems for vehicle ad-hoc networks using the virtual message ferry routing scheme

3. Value co-creation with Internet of things technology in the retail industry

4. Carbon emission management system of port logistics based on internet of things technology;D. Bo;Agro Food Industry Hi-Tech,2017

5. Forward and reverse logistics network and route planning under the environment of low-carbon emissions: A case study of Shanghai fresh food E-commerce enterprises

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2. Key Technology and Analysis of Expressway Intelligent Service Area;2022 IEEE 25th International Conference on Computer Supported Cooperative Work in Design (CSCWD);2022-05-04

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