Robust optimization of multi-scenario many-objective problems with auto-tuned utility function. Issue 7 (3rd July 2021)

• Record Type: Journal Article
• Authors: Kecskés, István; Odry, Péter
• Is Part Of: Engineering optimization. Volume 53:Issue 7(2021)
• Page Start: 1135
• Page End: 1155
• Publication Date: 2021-07-03
• Subjects: Robust optimum -- multi-scenario -- multi-objective optimization -- sensitivity analysis -- simulation model; Engineering design -- Periodicals; Mathematical optimization -- Periodicals; 620.0042
• DOI: 10.1080/0305215X.2020.1775823
• Languages: English
• ISSNs: 0305-215X

Abstract

ABSTRACT: The main focus in optimization studies, including multi-objective and multi-scenario optimization, is placed on finding the global optimum or global Pareto-optimal solutions, representing the best possible objective values. Manual preferences and selection are required to obtain a single implementable solution from the obtainable Pareto set. For achieving such a single optimum, the multi-scenario property is applied to adjust the required preference weights automatically; as a result, robust performance for various scenarios is provided. The robust quality definition is believed to decrease the performance uncertainty owing to any possible scenario in real-world settings. These challenges have motivated the creation of a method that searches a robust solution using evolutionary algorithms and well-applied IT tools. This selection process applies two robustness aspects simultaneously: the necessary weights for the aggregation of multi-scenario and multi-objective dimensions are adjusted to obtain similar performances for scenarios as much as possible; the robustness against system parameters is evaluated by the calculation of the robustness indices. The method can be used universally where the robust optimum is required for a model having multi-scenario and multi-objective properties. The proposed method has been tested on test functions, and in conclusion it has been applied to two engineering problems.