SEQUENCING OF ACTIVITIES IN CONCURRENT PROJECTS USING GENETIC ALGORITHMS.

The problem of task sequencing in concurrent projects with limited resources is critical in project management, as it involves the efficient allocation of scarce resources to minimize the total duration of projects (makespan). Complexity increases when multiple projects compete simultaneously for the same resources, requiring precise planning to avoid delays and ensure efficiency.

In this context, this paper presents a model for sequencing activities in simultaneous projects, using genetic algorithms and a chromosomal representation based on random keys. Unlike previous approaches, this research incorporates a tailored evaluation function that balances minimizing duration and maximizing efficiency in time management by considering multiple projects in an integrated way. Computational experiments with real data from different projects demonstrate the effectiveness of the model, highlighting the practical application and improvement in resource allocation in complex project management scenarios.