Air Pollution Based Vehicular Routing Problems: Using Genetic Algorithm Optimization Approach

The Vehicle Routing Problem is a unique and special kind of problem providing solution to the real world situation. Obviously it's a combinatorial optimization problems since the real-world significance and its complication. However in close look many methods have been suggested to solve the Vehicle Routing Problems efficiently. The respective methods has its own balance factors in terms of the performance. Other than regular balance factors like distance and time very few have studied about some real environmental factors since because of its limitation of data and implementation issues. From this viewpoint, an intelligent routing approach for Vehicle Routing Problem is proposed with the aim of dispose the air pollution intensity accumulated in the road side environments. The proposed approach uses a diverse model of Genetic Algorithm to find the optimal paths the nodes or cities under air-pollution intensity based optimized route estimation. Since there is no predefined solved optimal solution for air pollution routing, we created a test bed to generate its dataset respect to the Travelling Salesman Problem benchmark functions. Three well know initialization technique was used to seed the population into the Genetic Algorithm process. The experimental results are evident that the proposed methods creates new breakthrough in Genetic Algorithm specifically in the stream of environmental oriented optimization approach.