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MecSol 2017
6th International Symposium on Solid Mechanics
MOKO: AN OPEN SOURCE PACKAGE FOR MULTI-OBJECTIVE OPTIMIZATION WITH KRIGING SURROGATES
Submission Author:
Adriano Gonçalves dos Passos , PR
Co-Authors:
Marco Antonio Luersen
Presenter: Adriano Gonçalves dos Passos
doi://10.26678/ABCM.MecSol2017.MSL17-0053
Abstract
Many modern real-world designs rely on the optimization of multiple competing goals. For example, most components designed for the aerospace industry must meet some conflicting expectations. In such applications, low weight, low cost, high reliability, and easy manufacturability, are desirable. In some cases, bounds for these requirements are not clear, and performing a mono-objective constrained optimization might not provide a good landscape of optimal choices. For these cases, finding a set of Pareto optimal designs might give the designer a comprehensive set of options from where to choose the best design. This article shows the main features of an open source package, developed by the authors, to solve constrained multi-objective problems. The package, named 'moko' (Multi-Objective Kriging Optimization), was built under the open source programming language R. Popular Kriging based multi-objective optimization strategies, as the expected volume improvement and the weighted expected improvement, are available in the package. In addition, a novel approach based on the exploration using a predicted Pareto front is implemented. The latter approach showed to be more efficient than the remainder ones in some didactic and real-life multi-objective applications performed by the authors with 'moko'
Keywords
Multi-Objective Optimization, Surrogates, Kriging, Open Source Package
