A Hybrid Meta-Heuristic Algorithm for the Minimization of Software Development Multi-Project Schedule

T. Gonsalves and K. Itoh (Japan)


Simulation optimization, meta-heuristics, Particle SwarmOptimization, Ant Colony Optimization


The Software Development Multi-Project Scheduling Problem is similar to the well-known Resource Constrained Multi-Project Scheduling Problem (RCMPSP). It consists in determining a schedule of tasks taking into consideration resource availabilities and precedence constraints, while optimizing an objective. Like RCMPSP, it is an NP-hard problem. In this paper, a task segmentation scheme to schedule a software development project is proposed and the makespan of the multiple concurrent projects is minimized using a hybrid meta-heuristic algorithm consisting of the Particle Swarm Optimization (PSO) and the Ant Colony Optimization (ACO) meta-heuristics. The hybrid algorithm harnesses the outstanding features of both the individual constituent meta-heuristics leading to faster convergence and optimal results.

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