A Genetic Algorithm with an Adaptive Penalty Function for the Orienteering Problem

Abstract

This paper presents a genetic algorithm to solve the orienteering problem, which is concerned with finding a path between a given set of control points, among which a start and an end point are specified, so as to maximize the total score collected subject to a prescribed distance constraint. Employing several sets of test problems from the literature, the performance of the genetic algorithm is evaluated against problem specific heuristics and an artificial neural network optimizer