Royal Lineage Genetic Algorithm for a Better Solution to Traveling Salesman Problem

被引：0
|
作者：
Firdaus, Himma [1 ]
Widianti, Tri [1 ]
机构：
[1] Natl Res & Innovat Agcy Republ Indonesia, Res Ctr Testing Technol & Stand, Tangerang Selatan, Indonesia
来源：
2024 23RD INTERNATIONAL SYMPOSIUM INFOTEH-JAHORINA, INFOTEH | 2024年
关键词：
genetic algorithms; insertion algorithm; 2-opt heuristic; travelling salesman problem; royal lineage; 2-OPT ALGORITHM; HEURISTICS;
D O I：
10.1109/INFOTEH60418.2024.10496037
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Genetic Algorithms (GAs) are famous for solving real-world problems despite a tendency to converge prematurely. This paper introduces the Royal Lineage Genetic Algorithm (RoLiGA), a GA enhancement inspired by chromosomal inheritance in royal lineages. The RoLiGA employed several algorithms, including the insertion heuristic, elitist domination procedure, fitness-based-roulette selection, multi-prince family's regeneration, partially mapped crossover, repetitive 2-point swap mutation, and 2-opt heuristics. The combination ensures the chromosomal inheritance process leads to optimal solutions. Tested on 26 Traveling Salesman Problem (TSP) datasets, RoLiGA outperforms five GA-based hybrid algorithms, obtaining the best-known values and setting new benchmarks for solution quality.
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页数：6
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