A Comparative Study of Production Control Mechanisms using Simulation-based Multi-Objective Optimization

Amos H.C. Ng (1) , Jacob Svensson (1) , Anna Syberfeldt (1)

1 Virtual Systems Research Centre

There exist many studies conducted to compare the performance of different production control mechanisms (PCMs) in order to determine which one performs the best under different situations. Nonetheless, most of these studies suffer from the problems that the PCMs are not compared with their optimal parameter settings in a truly multi-objective context. This paper describes how different PCMs can be compared under their optimal settings through generating the Pareto-optimal frontiers, in form of optimal trade-off curves in the performance space, by applying evolutionary multi-objective optimization to simulation models. This concept is illustrated with a bi-objective comparative study of the four most popular PCMs in the literature, namely Push, Kanban, CONWIP and DBR, on an unbalanced serial flow line in which both control parameters and buffer capacities are to be optimized. Additionally, it introduces the use of normalized hypervolume as the quantitative metric and confidence-based significant dominance as the statistical analysis method to verify the differences of the PCMs in the performance space. While the results from this unbalanced flow line cannot be generalized, it indicates clearly that a PCM may be preferable in certain regions of the performance space, but not others, which supports the argument that PCM comparative studies have to be performed within a Pareto-based multi-objective context.

Mots clés: Physical Sciences

Domaines: Sciences de l'ingénieur [physics]

Amos H.C. Ng, Jacob Svensson, Anna Syberfeldt. A Comparative Study of Production Control Mechanisms using Simulation-based Multi-Objective Optimization. International Journal of Production Research, 2011, ⟨10.1080/00207543.2010.538741⟩. ⟨hal-00707579⟩