Improving Software Project Cost Estimation and Planning Accuracy Using Genetic Algorithms and Fuzzy Logic
Ajay Jaiswal, Jagdish Raikwal, Ratnesh Litoriya · International Journal of Software Engineering and Knowledge Engineering · 2025
Accurate software project cost estimation is essential for efficient resource allocation, risk management, and scheduling. Accuracy and generality are frequently lacking in traditional estimate models. To improve prediction accuracy, this study suggests a hybrid framework (Fuzzy + GA) that combines fuzzy logic and genetic algorithms. Evaluations were performed using reference datasets from Desharnais, Kitchenham, and Maxwell with RMSE values of 0.4531, 0.0312, and 0.0416 and R squared scores of 0.7513, 0.9512, and 0.9142, respectively. The model outperformed current techniques and demonstrated notable gains.