Adaptive Multi-objective Differential Evolution

Multi-objective optimization exists everywhere in real-world applications such as engineering, financial, and scientific applications, because the outcome is directly linked to cost, profit and/or many other criteria that have heavy impacts on performance, safety, environment, etc. It is difficult to provide an ultimate comparison among different outcomes via only one dimension, as the involved multiple criteria/ objectives are generally competing and non-commensurable. For example, a financial manager needs to take both return and risk into consideration when making an investment decision; an air traffic controller needs to consider both the reduction of system-level airspace congestion and the satisfaction of different stakeholders’ preferences.