A Fuzzy Genetic Algorithm for Single-Machine Scheduling and Flexible Maintenance Planning Integration under Human Resource Constraints

This research focuses on the problem of scheduling jobs on a single machine that requires flexible maintenance under human resource constraints. A fuzzy genetic algorithm that integrates production, maintenance, human resource availability and competence constraints is developed. This algorithm uses fuzzy logic to deal with uncertainties. Experiments show that the consideration of human resource constraints and uncertainties in the integrated and proactive scheduling allows proposing more realistic and applicable solutions.

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