Integrated Particle Swarm Optimization Technique for Cost estimation

  • Priyanka Kukreja, Sukhdip Singh


The research paper has provided better solution for software cost estimation optimization by integrating PSO technique. Initially the paper has represented the simulation of existing cost estimation model considering organic, semidetached and embedded models. However there have been several researches in field of software cost estimation but they did not optimize the cost. The research work is simulating various cost estimation models. Moreover the PSO has been integrated in cost estimation model in order to get better cost solution. The PSO is used for optimizing the parameters considered during cost estimation of software. PSO is found computationally cheaper and faster as compare to existing Genetic algorithm based model. NASA records have been used for examine the efficiency of planned model. Proposed PSO is better as compare to traditional cost estimation model and Genetic algorithm based cost estimation model. PSO tuned parameter provides better assessment in comparison to traditional cost estimation model. It is also faster as compare to existing GA based cost estimation model. It is possible to expand this work in the upcoming time to increase work of estimation model. Matlab has been used in simulation. The simulation is made for cost estimation model that is PSO dependent. Finally the comparison of proposed work is made with traditional research. Research is providing better platform to achieve best cost.

How to Cite
Priyanka Kukreja, Sukhdip Singh. (2020). Integrated Particle Swarm Optimization Technique for Cost estimation. International Journal of Advanced Science and Technology, 29(3), 11478 - 11484. Retrieved from