How Multi-Objective Genetic Programming Is Effective for Software Development Effort Estimation?

The idea of exploiting search-based methods to estimate development effort is based on the observation that the effort estimation problem can be formulated as an optimization problem. As a matter of fact, among possible estimation models, we have to identify the best one, i.e., the one providing the most accurate estimates. Nevertheless, in the context of effort estimation there does not exist a unique measure that allows us to compare different models and consistently derives the best one [1]. Rather, several evaluation criteria (e.g., MMRE and Pred(25)) covering different aspects of model performances (e.g., underestimating or overestimating) are used to assess and compare estimation models [1]. Thus, considering the effort estimation problem as an optimization problem we should search for the model that optimizes several measures. From this point of view, the effort estimation problem is inherently multi-objective. Nevertheless, all the studies that have been carried out so far on the use of search-based techniques for effort estimation exploited single objectives (e.g., [2][3]). Those studies have also revealed that the use of some measures as fitness function (e.g., MMRE) decreased a lot the accuracy in terms of other summar