ASimulated Logistic Algorithm for Distributed Flexible Assembly Flowshop Scheduling with Post-processing

An optimized mathematical model has been developed to streamline gas turbine production by targeting the minimization of the overall completion time, known as makespan. The production process is broken down into a series of stages: jobs are processed across multiple parallel factories, assembled into semi-finished goods with flexibility in their assembly order, and then transformed into final products through various stages of additional processing. To initiate solutions, a three-tier composite heuristic is employed, supplemented by six specialized neighborhood structures devised according to the different stages of the problem. Drawing inspiration from natural population growth mechanisms, we introduce a Simulated Logistic Algorithm (SLA) designed for robust solution enhancement. Comparative experiments on both small and extensive scales demonstrate the SLA's superior performance over established optimization techniques such as Particle Swarm Optimization, Tabu Search, and Genetic Algorithms, especially notable in large-scale applications. Thorough mathematical and statistical evaluations reinforce the efficacy of the SLA and validate the proposed approach.