Table 1.

Summary of literature studies [5],[6],[8],[9],[10],[13],[16],[17],[18],[19],[21],[22].

Author	Area	Method	Strength	Limitation
[5]	Optimization of Power Transmission Lines Routing	FAHP, GIS	Allow multi-inputs	Slow operation, lack of reliability, suitable for least number of routes only
[6]	Solving Large-scale TSP Problems	TSP-ACA	High robustness, high precision, simplicity	Slow operation, suitable to solve small and medium size of TSP problems only, suitable for singular TSP objective function only
[8]	Simulated Annealing in Maximizing the Thermal Conductance	SA	Simplicity, less restriction	Single-based solution
[9]	TSP Optimization using Genetic Algorithm	TSP-GA	High efficiency against complex problems	Suitable for singular TSP objective function only
[10]	XGBoost Optimized by Adaptive Particle Swarm Optimization for Credit Scoring	PSO	High efficiency,	High risk falling to local optimum region
[13]	Persistent Unmanned Aerial Vehicle Delivery Logistics	TSP-MILP	High efficiency, high flexibility	Not suitable for large-scale problems
[16]	Clustering for TSP Problems	Improved TSP-GA	High efficiency, able to handle large scale TSP problems with a shorter period	Suitable for singular TSP objective function only
[17]	Multiple TSP Problems	MTSP-PGA	High efficiency	Poor communication between individuals
[18]	Optimization with Fuzzy Control	FPSO-GA	High precision, search optimum results with high diversity	Complexity issue
[19]	Optimization of Carpool Service Problem	FGA	Short computation time, less complexity	Lack of flexibility
[21]	Cyber-attack on Overloading Multiple Lines	MILP	High efficiency, high Precision	Not suitable for large-scale problems, Suitable for singular TSP objective function only
[22]	Electrical Simulation Optimization Problems	MILP	High efficiency, short execution duration, high feasibility	Complexity issue

This research paper presented the improved hybrid AI algorithm to optimize the transmission line routes among 155 HES. The proposed AI algorithms are superior in integrating HES and work effectively in optimizing the multi-objective functions. Hence minimum values of total distance and elevation difference among 155 HES have been acquired. Furthermore, for the proposed algorithm architecture, fuzzy logic functions are developed to interact with multi-independent inputs, while the TSP-GA algorithm plays a crucial role in searching for the best transmission routing diversely from the global and local optimum regions.