Investigation of Vehicle Logistics Cost Control Model Based on Internet of Things Mode Based on E-commerce Platform

2021 ◽  
Vol 7 (5) ◽  
pp. 4763-4774
Author(s):  
Fengjuan Zhang
Keyword(s):  
Internet Of Things ◽  
Ant Colony Algorithm ◽  
Optimal Algorithm ◽  
Cost Effective ◽  
Ant Colony ◽  
Continuous Increase ◽  
The Sustainable Development ◽  
Logistics Enterprises ◽  
Scheduling Plan ◽  
The Cost

Objectives: The rise of the Internet of Things and e-commerce platform has enabled logistics companies to embark on a fast-growing road. How to effectively control the cost of vehicle transportation under the condition of continuous increase in the total volume of logistics business is the key to influencing the sustainable development of logistics enterprises. Methods: In order to reduce the cost of vehicle transportation, the use of artificial intelligence ant colony algorithm to build intelligent deployment model is explored. Results: After analyzing the principle and implementation flow of the traditional ant colony algorithm, the ant colony algorithm is updated and optimized from the perspective of many dynamic factors and large changes in the logistics vehicle. Conclusion: A combination of optimal algorithm parameters is constructed to help logistics companies find the most cost-effective vehicle scheduling plan. Simulation tests show that the optimized ant colony algorithm can quickly find the optimal cost-effective route and effectively control the vehicle logistics costs.

scholarly journals Clustering Control of Multi-Objective Problems with Application to E-commerce

2018 ◽  
Vol 1 (1) ◽  
pp. 41
Author(s):  
Liang Chen ◽  
Xingwei Wang ◽  
Jinwen Shi
Keyword(s):  
Ant Colony Algorithm ◽  
Time Window ◽  
Ant Colony ◽  
Distribution Area ◽  
Routing Problem ◽  
Logistics Distribution ◽  
Multi Objective ◽  
The Cost ◽  
Vehicle Capacity ◽  
Cost Of Transportation

In the existing logistics distribution methods, the demand of customers is not considered. The goal of these methods is to maximize the vehicle capacity, which leads to the total distance of vehicles to be too long, the need for large numbers of vehicles and high transportation costs. To address these problems, a method of multi-objective clustering of logistics distribution route based on hybrid ant colony algorithm is proposed in this paper. Before choosing the distribution route, the customers are assigned to the unknown types according to a lot of customers attributes so as to reduce the scale of the solution. The discrete point location model is applied to logistics distribution area to reduce the cost of transportation. A mathematical model of multi-objective logistics distribution routing problem is built with consideration of constraints of the capacity, transportation distance, and time window, and a hybrid ant colony algorithm is used to solve the problem. Experimental results show that, the optimized route is more desirable, which can save the cost of transportation, reduce the time loss in the process of circulation, and effectively improve the quality of logistics distribution service.

Smart Healthcare

2018 ◽  
pp. 21-33
Author(s):  
R. Rajkumar
Keyword(s):  
Internet Of Things ◽  
Real Time ◽  
Cost Effective ◽  
Reliable System ◽  
Smart Healthcare ◽  
Cloud Server ◽  
Android App ◽  
The Cost ◽  
Very High ◽  
At Home

Internet of things is a revolutionary domain, when we use it for the wellness of people in a smart way. As of now, the cost to implement IoT-enabled services is very high. So, this chapter introduces a cost effective and a reliable system to monitor patients at home and in hospitals with the help of IoT. The monitored details of a person can be drawn at any time with the help of an android app, which can produce output at real-time. The processed data are stored in the UBIDOTS cloud server, and the patients' needs can be met in time as well lives saved during critical cases with the help of the system proposed in this chapter.

Conclusions

2020 ◽  
pp. 296-304
Author(s):  
James Leigland
Keyword(s):  
Developing Countries ◽  
Private Investment ◽  
Cost Effective ◽  
The Political ◽  
The Sustainable Development ◽  
Fundamental Causes ◽  
Development Goals ◽  
The Cost ◽  
Technical Capacity ◽  
Poor Infrastructure

For reasons discussed in preceding chapters, public–private partnerships (PPPs) are unlikely to have major positive impacts on achievement of the Sustainable Development Goals (SDGs) or on the provision of transformational regional infrastructure, as envisioned by the G20. PPPs will continue to play modest but still important roles in the cost-effective provision of infrastructure service in many developing countries, as long as they are well structured, appropriately supported, and carefully monitored and evaluated. But PPPs made sustainable with large measures of concessional finance will do a disservice in the developing world if they distract from the fact that the fundamental causes of poor infrastructure service delivery in developing countries have very little to do with the availability of private investment. Those causes involve things like government policies, institutions, technical capacity, as well as the political economy realities of these countries and their relationships with development partners

The Research on VRP Based on Max-Min Ant Colony Algorithm

2011 ◽  
Vol 219-220 ◽  
pp. 1285-1288 ◽  
Author(s):  
Chang Min Chen ◽  
Wei Cheng Xie ◽  
Song Song Fan
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Ant Colony Algorithm ◽  
Search Time ◽  
Ant Colony ◽  
Local Optimum ◽  
Simulation Data ◽  
Routing Problem ◽  
Np Hard Problem ◽  
The Cost

Vehicle routing problem (VRP) is the key to reducing the cost of logistics, and also an NP-hard problem. Ant colony algorithm is a very effective method to solve the VRP, but it is easy to fall into local optimum and has a long search time. In order to overcome its shortcomings, max-min ant colony algorithm is adopted in this paper, and its simulation system is designed in GUI of MATLAB7.0. The results show that the vehicle routing problem can well achieves the optimization of VRP by accessing the simulation data of database.

Research on Application of Ant Colony Optimization

2014 ◽  
Vol 548-549 ◽  
pp. 1213-1216
Author(s):  
Wang Rui ◽  
Zai Tang Wang
Keyword(s):  
Ant Colony Optimization ◽  
Optimization Algorithm ◽  
Ant Colony Algorithm ◽  
Optimal Algorithm ◽  
Convergence Speed ◽  
Ant Colony ◽  
Ant Colony Optimization Algorithm ◽  
Slow Convergence ◽  
Simulation Results ◽  
Research On Application

We research on application of ant colony optimization. In order to avoid the stagnation and slow convergence speed of ant colony algorithm, this paper propose the multiple ant colony optimization algorithm based on the equilibrium of distribution. The simulation results show that the optimal algorithm can have better balance in reducing stagnation and improving the convergence.

Improved Ant Colony Algorithm Using in Design of the New Internet of Things Storage Mailbox System

2013 ◽  
Vol 753-755 ◽  
pp. 2845-2848
Author(s):  
Ke Wang Huang
Keyword(s):  
Internet Of Things ◽  
Ant Colony Algorithm ◽  
Ant Colony ◽  
The Internet ◽  
User Selection ◽  
The Internet Of Things ◽  
Improved Ant Colony Algorithm ◽  
Selection Of

The paper focuses on improved ant colony algorithm using in design of the internet of things storage and mailbox system. The improved ant colony algorithm solves the problems of the location of the storage mailbox mounting and user selection of optimal delivery.

scholarly journals OPTIMASI RUTE PANDUAN INFORMASI LOKASI WISATA MENGGUNAKAN ANT COLONY SYSTEM PADA KOTA BATAM

2019 ◽  
Vol 2 (2) ◽  
pp. 1-13
Author(s):  
Alfannisa Annurrallah Fajrin ◽  
Delia Meldra
Keyword(s):  
Ant Colony Algorithm ◽  
Path Selection ◽  
Ant Colony ◽  
Ant Colony System ◽  
Tourist Attractions ◽  
Tourist Destinations ◽  
The People ◽  
Waterfall Model ◽  
The Cost ◽  
The City

The number of tourists visiting the city of Batam both domestic and foreign tourists to spend their vacation time because the cost of living and goods are cheaper than other areas because batam is an FTZ area (free tax Zone). So that the city of Batam has become a shopping paradise for the people around Batam or outside Batam. Batam itself has several shopping destinations and places to visit for tourists. With the abundance of tourist destinations in the city of Batam, both shopping and nature tourism, it is not uncommon for tourists to experience various problems in visiting the country, one of the simple problems experienced is the problem of time and cost efficiency in conducting tours to the city of Batam. The problem that we can solve in this research is to help tourists or tourists not experience difficulties when visiting tourist attractions in Batam by using the ant colony algorithm in efficient path selection. The Waterfall Model in SDLC is a process that will be used in this study to get the best results.

scholarly journals Research on Optimal Matching Scheme of Public Resource Management Based on the Computational Intelligence Model

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Linna Li ◽  
Renjun Liu
Keyword(s):  
Genetic Algorithm ◽  
Human Resources ◽  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Time Consumption ◽  
Public Resource ◽  
Public Resources ◽  
Benefit Function ◽  
The Cost ◽  
Better Than

The management of public resources means that people’s governments at all levels and other public administrative subjects should use certain means and methods, follow certain principles, rationally allocate and utilize public resources, and maximize their functions and benefits. Under the background of limited human resources, this study adheres to the principle of maximizing the benefits of human resources and rationally allocates the use of human resources. In this study, this kind of resource allocation problem is regarded as a linear programming problem by specifying the benefit function, and then, genetic algorithm, ant colony algorithm, and hybrid genetic-ant colony algorithm are used to solve the problem; the cost and time consumption of different algorithms under different scales are evaluated. Finally, it is found that genetic algorithm is superior to ant colony algorithm when the task scale is small and the effect of genetic algorithm is lower than ant colony algorithm with the expansion of task scale, whereas the improved hybrid genetic-ant colony algorithm is better than ordinary algorithm in general.

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