Density Function-Based Trust Region Algorithm for Approximating Pareto Front of Black-Box Multiobjective Optimization Problems
- Authors: Ju K.H.1, O Y.B.1, Rim K.1
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Affiliations:
- Department of Mathematics, Kim Il Sung University
- Issue: Vol 63, No 12 (2023)
- Pages: 2156-2156
- Section: ОПТИМАЛЬНОЕ УПРАВЛЕНИЕ
- URL: https://journals.rcsi.science/0044-4669/article/view/233044
- DOI: https://doi.org/10.31857/S0044466923120189
- EDN: https://elibrary.ru/AQCHHV
- ID: 233044
Cite item
Abstract
In this paper, we consider a black-box multiobjective optimization problem, whose objective functions are computationally expensive. We propose a density function-based trust region algorithm for approximating the Pareto front of this problem. At every iteration, we determine a trust region and then in this trust region, select several sample points, at which are evaluated objective function values. In order to obtain non-dominated solutions in the trust region, we convert given objective functions into one function: scalarization. Then, we construct quadratic models of this function and the objective functions. In current trust region, we find optimal solutions of all single-objective optimization problems with these models as objectives. After that, we remove dominated points from the set of obtained solutions. In order to estimate the distribution of non-dominated solutions, we introduce a density function. By using this density function, we obtain the most “isolated” point among the non-dominated points. Then, we construct a new trust region around this point and repeat the algorithm. We prove convergence of proposed algorithm under the several assumptions. Numerical results show that even in case of tri-objective optimization problems, the points generated by proposed algorithm are uniformly distributed over the Pareto front.
About the authors
K. H. Ju
Department of Mathematics, Kim Il Sung University
Email: math9@ryongnamsan.edu.kp
Democratic People’s Republic of Korea, CITY
Y. B. O
Department of Mathematics, Kim Il Sung University
Email: math9@ryongnamsan.edu.kp
Democratic People’s Republic of Korea, CITY
K. Rim
Department of Mathematics, Kim Il Sung University
Author for correspondence.
Email: math9@ryongnamsan.edu.kp
Democratic People’s Republic of Korea, CITY