A new approach by using Tabu search and genetic algorithms in Software Cost estimation

Software Cost estimation (SCE) is an important and necessary issue before starting any software project. Because before starting any software project, we must know the real needs of software implementation cost, required time, required manpower and etc. In fact, the purpose of SCE is that the estimated cost differs slightly with actual cost. Accurate estimation of software projects has been always one of the managers' perturbation, therefore researchers have been trying to optimize SCE by using different methods and algorithms. By studying the previous works in this field, we find that a lot of works has been done by many researchers, and efficient methods have been provided, but none of them can do completely and 100% accurate estimation. Considering the benefits of metaheuristic algorithms in SCE, we used hybrid of Genetic algorithm and Tabu search algorithm that are types of metaheuristic algorithms could play a significant role in engineering optimization issues in this paper. This results show that, more optimum results had been obtained in SCE by using the hybrid of Tabu search algorithm and genetic algorithm.