Ant-Colony-Algorithm-Based Intelligent Transmission Network Planning

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.