Furniture Production Optimization with Visual Simulation and Genetic Algorithms

摘要

The paper is dealing with a real case customized flexible furniture production optimization, represented as a job shop scheduling problem with recirculation where furniture is produced in very small or no series at all. Such a make-to-order production must be flexible to meet the customer's needs, which are changing frequently. Frequent review of the production process is needed to ensure near-optimal production schedule to meet the minimal makespan constraint. Optimization algorithm must be fast enough to ensure the production schedule in real-time. Genetic algorithms were used as an optimization method. The visual model of the furniture production process was developed during the research. Such a model is closer to end-user perception and is used to clarify the results of numerical optimization. It also enables the implementation of end-user's expert knowledge into the optimizer to reduce the GA search space with a goal of reducing the runtime to a minimum.