Multi-Objective Optimization of Dynamic Systems and Problem of The Pareto Front Control

被引:1
|
作者
Romanova, I. K. [1 ]
机构
[1] Bauman Moscow State Tech Univ, Moscow 105005, Russia
关键词
D O I
10.1063/1.5133250
中图分类号
P1 [天文学];
学科分类号
0704 ;
摘要
The problem of a multi-level search for compromise solutions in the problem of a multi-objective optimization of dynamic systems is formulated. A distinctive feature of a dynamic system is its parameters changing over time. This changing can be either deterministic or stochastic. It is demonstrated that the quality indicators exist not only for the main optimized dynamic system, but also for the corresponding set of compromise solutions that form the Pareto front. In the frame of the multi-objective optimization theory and practice with the respect to the Pareto-optimal variants estimation the problem of active joint participation of the system creators and (or) decision makers (DM) in the Pareto front management is formulated. It is noted, that such problem formulation differs from the traditional approach which is based on the analysis of the already existing solutions. The possibilities to influence on the Pareto front in the frame of the parametric synthesis of double loop flight control system are exhibited. The paired criteria in the class of the direct quality criteria as well as in the integral criteria class are examined. The Pareto ranks structure as well as their dependence on the regulator properties is defined. A flight vehicle specific physical parameters the change of which in the frame of the new system design allows to achieve the best effects on the overall improvement of the compromise solutions are specified. The analytical dependencies that allow to estimate the limits of the possible improvement of the quality criteria are observed.
引用
收藏
页数:9
相关论文
共 50 条
  • [1] Direct Tracking of the Pareto Front of a Multi-Objective Optimization Problem
    Peri, Daniele
    JOURNAL OF MARINE SCIENCE AND ENGINEERING, 2020, 8 (09)
  • [2] Pareto Front Upconvert on Multi-objective Building Facility Control Optimization
    Okumura, Naru
    Takagi, Tomoaki
    Ohta, Yoshihiro
    Sato, Hiroyuki
    PROCEEDINGS OF THE 2023 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE COMPANION, GECCO 2023 COMPANION, 2023, : 1963 - 1971
  • [3] Using a Family of Curves to Approximate the Pareto Front of a Multi-Objective Optimization Problem
    Martinez, Saul Zapotecas
    Sosa Hernandez, Victor A.
    Aguirre, Hernan
    Tanaka, Kiyoshi
    Coello Coello, Carlos A.
    PARALLEL PROBLEM SOLVING FROM NATURE - PPSN XIII, 2014, 8672 : 682 - 691
  • [4] Using a family of curves to approximate the pareto front of a multi-objective optimization problem
    Martínez, Saúl Zapotecas
    Sosa Hernández, Víctor A.
    Aguirre, Hernán
    Tanaka, Kiyoshi
    Coello Coello, Carlos A.
    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2014, 8672 : 682 - 691
  • [5] A survey on pareto front learning for multi-objective optimization
    Kang, Shida
    Li, Kaiwen
    Wang, Rui
    JOURNAL OF MEMBRANE COMPUTING, 2024,
  • [6] Representation of the pareto front for heterogeneous multi-objective optimization
    Thomann J.
    Eichfelder G.
    Journal of Applied and Numerical Optimization, 2019, 1 (03): : 293 - 323
  • [7] Optimization over the Pareto front of nonconvex multi-objective optimal control problems
    Kaya, C. Yalcin
    Maurer, Helmut
    COMPUTATIONAL OPTIMIZATION AND APPLICATIONS, 2023, 86 (03) : 1247 - 1274
  • [8] Optimization over the Pareto front of nonconvex multi-objective optimal control problems
    C. Yalçın Kaya
    Helmut Maurer
    Computational Optimization and Applications, 2023, 86 : 1247 - 1274
  • [9] Analysis of the Pareto Front of a Multi-objective Optimization Problem for a Fossil Fuel Power Plant
    Van Sickel, Joel H.
    Venkatesh, Paramasivam
    Lee, Kwang Y.
    2008 IEEE POWER & ENERGY SOCIETY GENERAL MEETING, VOLS 1-11, 2008, : 1109 - 1116
  • [10] DEEP CONVOLUTIONAL NEURAL NETWORKS FOR PARETO OPTIMAL FRONT OF MULTI-OBJECTIVE OPTIMIZATION PROBLEM
    Liu, Ruilin
    Zhang, Tao
    Chen, Fang
    JOURNAL OF NONLINEAR AND CONVEX ANALYSIS, 2022, 23 (04) : 833 - 846