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An Efficient Evolutionary Algorithm for Chance-constrained Bi-objective Stochastic Optimization and Its Application to Manufacturing Engineering

<22> This paper presented the first efficient solution method for chance-constrained bi-objective stochastic optimisation problem, which is widely appeared in engineering design and manufacturing optimisation area. Novel speed enhancement techniques for Monte-Carlo simulation-embedded multi-objective optimisation problems have been developed. A real-world problem of the bi-objective variation-aware sizing for an analogue integrated circuit showed that much better results were obtained within 4 days compared to using the conventional optimisation methods with more than one month’s computational effort.