Reference point based evolutionary multi-objective optimization with dynamic resampling for producti

Ng, A. H. C., Siegmund, F., & Deb, K. (2018). Reference point based evolutionary multi-objective optimization with dynamic resampling for production systems improvement. Journal of Systems and Information Technology, 20(4), 489–512.


Abstract

Purpose – Stochastic simulation is a popular tool among practitioners and researchers alike for quantitative analysis of systems. Recent advancement in research on formulating production systems improvement problems into multi-objective optimizations has provided the possibility to predict the optimal trade-offs between improvement costs and system performance, before making the final decision for implementation. However, the fact that stochastic simulations rely on running a large number of replications to cope with the randomness and obtain some accurate statistical estimates of the system outputs, has posed a serious issue for using this kind of multi-objective optimization in practice, especially with complex models. Access publication

Initiators

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