A Multi-objective Genetic Algorithm for the Software Project Scheduling Problem

The software project scheduling problem considers the assignment of employees to project tasks with the aim of minimizing the project cost and delivering the project on time. Recent research takes into account that each employee is proficient in some development tasks only, which requiere specific skills. However, this cannot be totally applied in the Mexican context due to software companies do not categorize their employees by software skills, but by their skill level instead. In this study we propose a model that is closer to how software companies operate in Mexico. Moreover, we propose a multi-objective genetic algorithm for solving benchmark instances of this model. Results show that our proposed genetic algorithm performs similarly to two recent approaches and that it finds better multi-objective solutions when they are compared to those found by a well-known multi-objective optimizer. keywords Search-based software engineering, software project scheduling problem, genetic algorithm, multi-objective optimization.