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Recent Advances in Electrical & Electronic Engineering

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ISSN (Print): 2352-0965
ISSN (Online): 2352-0973

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Research Article

Ant-Colony-Algorithm-Based Intelligent Transmission Network Planning

Author(s): Jingzhong Yuan, Jia Guo, Jinghai Xie, Shihua Lu, Dongyu Su, Mi Sun and Mohd Asif Shah*

Volume 16, Issue 2, 2023

Published on: 04 October, 2022

Page: [120 - 125] Pages: 6

DOI: 10.2174/2352096515666220530113937

Price: $65

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Abstract

Background: The efficiency of wireless sensor networks is limited by limitations in energy supply. Efficient routing strategies should be designed to save and balance the energy consumption of each node in a wireless sensor network.

Aim: In this study, a transmission network based on an ant colony algorithm was proposed to meet the power load demands of a city.

Objective: Based on the chaos ant colony algorithm, using a combination of wireless sensor network and node residual energy factors, a neighbor selection strategy was proposed.

Results: The optimal result was 1896, and additional lines were: N14-15= 2, N4-16= 1, N5-12= 2, N7-13= L, N6-14= 1, N7-8. The coding method of solving transmission network planning based on multi-stage and multi-dimensional control variables was employed to decompose each control variable into two variables. The sum of total weight and non-zero bits was transformed into high-dimensional variables in state transition probability.

Conclusion: The key analysis showed that the ant colony algorithm, as a simulated evolutionary algorithm, is an efficient internal heuristic method.

Keywords: Ant colony algorithm, intelligent transmission network, power load, optimization, evolutionary algorithm, wireless sensor network.

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