Analysis of Genetic Parameters and Operators in Solving Looping and No Looping Shortest Path

Abstract

Studies on shortest paths are significantly impactful given its wide range of applications especially in transportation and route planning. This study provides an additional solution to various existing optimizationmethods by proposing a Genetic Algorithm (GA) approach incorporated with Haversine formula to find the solution to shortest path problems. Two cases are taken into account, namely Looping Shortest Path (LSP) and No Looping Shortest Path (NLSP). The algorithm is tested for a road map containing 20, 30, and 40 cities. The experiment is repeated several times to find the best combination of genetic parameters and operators for the problem under consideration.