An Adaptive Evolutionary Algorithm for Production Planning in Wood Furniture Industry

Abstract

This paper describes an adaptive evolutionary approach to the problem of the production planning task in the wood furniture industry. The objective is to schedule new incoming orders and to regenerate the scheduling for already existing orders when necessary. Complexity and uncertainty of this task promotes the use of an hybrid solution that combines evolutionary algorithms (EAs) and fuzzy sets. On one hand, EAs allow an efficient and flexible use of large number of parameters involved in the scheduling task and to reduce its computation time. On the other hand, fuzzy sets improve the confidence in the evaluation of the solutions when uncertain knowledge is used. This evolutionary approach to the production planning task is a part of a knowledge-based system that manages the product design life cycle of wood-based furniture and is being currently implemented on a wood furniture industry