Optimisation: Improving problem formulation and human interaction

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By Dr. Lucy Allan, Corey Grigg, Neil Cantle | 30. Juni 2017
Optimisation problems have traditionally been formulated as single objective and solved with the use of gradient-based or direct search methods. Most practical real-world problems involve multiple, often conflicting objectives, and also highly complex search spaces. Competing goals and objectives necessarily give rise to a set of compromise options and solutions. To counteract some of these difficulties, multiple-criteria decision-making is brought together with evolutionary multi-objective optimisation.