Key Issues in Real-World Applications of Many-Objective Optimisation and Decision Analysis

Abstract

The insights and benefits to be realised through the optimisation of multiple independent, but conflicting objectives are well recognised by practitioners seeking effective and robust solutions to real-world application problems. Key issues encountered by users of many-objective optimisation (>3 objectives) in a real-world environment are discussed here. These include how to formulate the problem and develop a suitable decision-making framework, together with considering different ways in which decision-makers may be involved. Ways to manage the reduction of computational load and how to reduce the sensitivity of candidate solutions as a result of the inevitable uncertainties that arise in real-world applications are addressed. Other state-of-the-art topics such as the use of machine learning and the management of complex issues arising from multidisciplinary applications are also examined. It is recognised that optimisation in real-world applications is commonly undertaken by users and decision-makers who need not have specialist expertise in many-objective optimisation decision analysis methods. Advice is offered to experts and non-experts alike.