Immune and Multi-agent systems for Flow shop scheduling

This book presents a new mutation operator that integrates principles from artificial immune systems (AIS) and multi-agent systems, with the aim of optimizing preventive maintenance planning in hybrid flow shop environments.The operator introduces slight adjustments in sequences to avoid convergence to local optima, improve population diversity and act as a local search mechanism. Inspired by the adaptive behavior of the human immune system, the approach uses metaheuristic techniques to refine processing times, combining multi-agent coordination with AIS-inspired strategies.The method is applied to three preventive maintenance policies, focused on maximizing machine availability and meeting minimum reliability thresholds in production lines. Results show that the algorithm outperforms existing solutions, particularly in scenarios where machines experience periodic unavailability during production planning.