Optimizing concurrent configuration and planning: A proposition to reduce computation time

Abstract

This communication deals with mass customization and the association of the product configuration task with the planning of its production process while trying to optimize cost and cycle time. In some previous works, we have proposed an optimization algorithm, called CFB-EA. This communication concerns a way to improve CFB-EA for large problems. Previous experiments have highlighted that CFB-EA is able to find quickly a good approximation of the Pareto Front. This led us to propose to decompose the optimization in two tasks. First, a “rough” approximation of the Pareto Front is quickly searched and proposed to the user. Then the user indicates the area of the Pareto Front that he is interested in. The problem is filtered and the solution space reduced. A second optimization is launched on the focused area. Our goal is to compare the classical single task optimization with the two tasks proposed approach.