Abstract
In the current market, engineers are continually required to optimize their designs to realise improved performance whilst meeting ever more stringent regulations and competing for market share. This reality increases the demand for optimization. Due to these, and several other reasons, real-world optimization problems often have a large search space, are non-convex, and have expensive-to-evaluate objective functions that have many conflicting objectives. However, even if these problems are overcome, to select an acceptable solution, the decision making process itself is equally demanding. Some of these difficulties could be alleviated if a tool existed to support the analyst and decision maker throughout the entire process. The aim of this work is to illustrate and share insight gained in using Liger in such a scenario. Liger is an open source integrated optimization environment and its use is described in a case study of involving the calibration of a diesel engine using multi-models. The benefits of using Liger are demonstrated along with the procedure we followed to obtain an optimized engine calibration that complies with performance and regulatory requirements.
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Giagkiozis, S., Lygoe, R.J., Giagkiozis, I., Fleming, P.J. (2015). Diesel Engine Drive-Cycle Optimization with Liger. In: Gaspar-Cunha, A., Henggeler Antunes, C., Coello, C. (eds) Evolutionary Multi-Criterion Optimization. EMO 2015. Lecture Notes in Computer Science(), vol 9019. Springer, Cham. https://doi.org/10.1007/978-3-319-15892-1_22
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DOI: https://doi.org/10.1007/978-3-319-15892-1_22
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