Shipbuilding Planning Under Uncertainty: Application of Genetic Algorithms and Fuzzy Logic for Efficient Resource Scheduling of Projects
DOI:
https://doi.org/10.70577/6mmaxz43Keywords:
Algoritmos Genéticos (AG), Lógica Difusa, Optimización Multiobjetivo, Análisis de Sensibilidad, Toma de DecisionesAbstract
This study examines the application of Genetic Algorithms (GA) in optimizing production processes in shipbuilding, considering environments characterized by high levels of uncertainty. The research addresses two fundamental aspects: first, the integration of the Resource-Constrained Project Scheduling Problem (RCPSP) using GA in combination with uncertainty management techniques applied to shipbuilding production; and second, the analysis of Pareto optimal solutions generated by genetic algorithms to achieve efficient scheduling in this context.The proposed methodological framework aims to minimize the total project completion time and maximize the utilization of available resources by incorporating probabilistic models and scenario analysis to effectively address uncertainties present in the production environment. Furthermore, the study focuses on evaluating trade-offs between project completion time, resource allocation, and costs through the analysis of Pareto optimal solutions, using visualization techniques and sensitivity analysis to support strategic decision-making.The results contribute to improving efficiency in shipbuilding production by providing a comprehensive approach that enables more effective uncertainty management, better resource allocation, and a significant reduction in project duration through the integration of the RCPSP approach with genetic algorithms and advanced uncertainty analysis techniques
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