A comparison of the efficiency between Genetic Algorithms and Particle Swarm Optimization Algorithm for Solving VRP

Abstract

This study the research relies Genetics Algorithms theory comparison with Particle Swarm Optimization for solving the Vehicle Routing Problem in finding a good solution having a good starting point. The Concept Genetics Algorithms theory the best answer is determined by information in the form of chromosomes are genetic inheritance from ancestors to descendant’s whit fitness function complies with the purpose Objective function. These steps, it is possible to find the answer with the highest (minimum) value. The answer using chromosome in each generation, which has a random answer to all candidate solution.

The Particle Swarm Optimization; PSO to find the answer at Random Search Algorithm, as well as to answer genetic algorithm analysis. The program that created the basis for a revised set of psychological principles simple answer. The basic truth is put into a computer program.

The results showed that GAs propagation applied to PSO can reduce or fix local installation problems Optics and be able to optimize find the answers of PSO for solving VRP by receiving an appropriate response in a faster time period than the normal GAs and PSOs