GlobeTrotter: An Optimal Travel Sequence Generator

The ready-made fixed packages provided by travel firms has always been a setback when tourists sought to find a travel experience that is customized to their own needs. The situation then demands for a system that provides a tailor made optimized travel sequence. For that we propose a system wherein a recommendation system is employed to recommend popular places to the user. An optimized travel sequence is then generated from these selected places using optimization algorithms that consists of two popular meta-heuristics techniques; Ant Colony Optimization (ACO) and Genetic Algorithm (GA). In this work, we compare both and use the best algorithm of the two for the final solution.

I. Introduction

In the current scenario, fixed travel itineraries are provided to the customers by the travel agencies with less or no consent of the user. This problem persists with most of the current travel agencies who resort to traditional methods. Traditional travel services have these drawbacks: 1)

Itineraries are pre made and not tailored to the interest of an individual.

2)

They are rarely updated.