Using constraints filtering and evolutionary algorithms for interactive configuration and planning

Abstract

This communication aims to associate the product configuration task with the planning of its production process in order to make consistent decisions while trying to minimize cost and cycle time. A two step approach is described with relevant aiding tools. During the first one, configuration and planning are considered as two constraint satisfaction problems and are interactively assisted by constraint propagation. The second one, thanks to a multicriteria optimisation relying on a constrained evolutionary algorithm, proposes a set of solutions belonging to a Pareto front minimizing cost and cycle time to the user. After a problem introduction and a global description of the aiding system, the paper focuses on the optimisation process with interesting quantified results.Keywordsproduct configuration, process planning, constraint satisfaction problem, evolutionary algorithm 978-1-4244-8503-1/10/$26.00 ©2010 IEEE Proceedings of the 2010 IEEE IEEM

Some Experimental Results Relevant to the Optimization of Configuration and Planning Problems

“…However classic evolutionary algorithms have to be adapted in order to take into account the constraints of the problem as explained in [10]. Among these adaptations, the one we have proposed in [3] is an evolutionary algorithm with a specific constrained evolutionary operators and our goal is to compare it with a classical branch and bound approach.…”

“…In this case a limited backtrack process is launched to solve the problem. For full details please see [3]. The key idea of the Branch and Bound algorithm is to explore a search tree but using a cutting procedure that stops exploration of a branch when a better branch has already been found.…”

“…Meanwhile some scientific works have been published on this subject (see for example [1] or [2]) and the focus of this article is on the optimization problem. In some previous conferences we proposed an interesting adapted evolutionary algorithm for this problem [3]. However, the presentation was rather descriptive and experimentations were not significant.…”