COST OPTIMIZATION FOR TRAVELLING SYSTEM EMPLOYING GENETIC ALGORITHM (WAY-PLANNER APP)

Abstract

Logistics by any means is the fastest growing sector around the globe and yet the most underrated and condoned of all. One ofthe typical problems is travel salesman problem, where one must travel multiple destinations with as much less cost and time as possible. This is the main reason we have initiated our “WayPlanner” project. The main objective here is to estimate a pathway for those destinations in such a way that the cost and time is to be as minimum as possible hence to be optimal. The planner will tend to provide the user with optimal route for the journey. As the number of destinations increases the complexity also gets increased exponentially which normal human mind cannot calculate. The core mechanism behind this project is to develop an evolutionary algorithm which can calculate the possibilities and provide with the best result. Currently some famous names are to be known that provides the service for travelling from some source to some destination like Uber, Careem, AirLift and Bykea. But neither of them provides the solution for the TSP problem. Proper researches are being made still for this problem as an ideal solution is not yet discovered. So, the goal would be to meet as much accuracy as possible. Many search algorithms can be nominated to play the required part, Genetic Algorithm be a potential solution for this problem. Later, in the report, we have encapsulated all findings regarding the project, our scope, motivations, methodologies and objectives.