4.7 Article

A performance approximation assisted expensive many- objective evolutionary algorithm

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Article Engineering, Aerospace

Flexible Task Scheduling in Data Relay Satellite Networks

Guohua Wu et al.

Summary: This paper proposes a novel application mode and algorithm for task scheduling in data relay satellite networks. Experimental results demonstrate the competitive performance of the proposed algorithm in terms of task completion ratio.

IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS (2022)

Article Automation & Control Systems

Ensemble Many-Objective Optimization Algorithm Based on Voting Mechanism

Wenbo Qiu et al.

Summary: The research proposes a general voting-mechanism-based ensemble framework (VMEF) that integrates and cooperates different solution-sorting methods to achieve more robust solution selection. The framework employs a strategy to adaptively allocate total votes based on the contribution of each solution-sorting method, providing good feedback for the optimization process.

IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS (2022)

Article Computer Science, Artificial Intelligence

An effective iterative greedy algorithm for distributed blocking flowshop scheduling problem with balanced energy costs criterion

Xue Han et al.

Summary: In this paper, a distributed blocking flowshop scheduling problem with sequence-dependent setup times (DBFSP_SDST) is proposed to address the distributed flowshop scheduling problem (DPFSP) with blocking constraints and sequence-dependent setup times (SDST). The goal is to minimize the energy consumption cost of the critical factory under resource balance. An effective iterated greedy algorithm based on a learning-based variable neighborhood search algorithm (VNIG) is developed to solve this problem. Extensive simulation experiments demonstrate the superior performance of the proposed VNIG compared to other algorithms.

APPLIED SOFT COMPUTING (2022)

Article Computer Science, Artificial Intelligence

A surrogate-ensemble assisted expensive many-objective optimization

Yi Zhao et al.

Summary: This paper proposes a method to train multiple surrogate models to assist many-objective optimization algorithm for solving expensive many-objective problems. Experimental results show that this method is competitive with other surrogate-assisted evolutionary algorithms within a limited computational budget.

KNOWLEDGE-BASED SYSTEMS (2021)

Article Computer Science, Artificial Intelligence

A Kriging-Assisted Two-Archive Evolutionary Algorithm for Expensive Many-Objective Optimization

Zhenshou Song et al.

Summary: The proposed algorithm uses Kriging-assisted two-archive EA for expensive many-objective optimization, employing an influential point-insensitive model to approximate each objective function and proposing an adaptive infill criterion for determining an appropriate sampling strategy. Experimental results have shown its superiority over five state-of-the-art SAEAs on a set of expensive multi/many-objective test problems.

IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION (2021)

Article Computer Science, Artificial Intelligence

Evolutionary many-Objective algorithm based on fractional dominance relation and improved objective space decomposition strategy

Wenbo Qiu et al.

Summary: The traditional Pareto-dominance-based many-objective evolutionary algorithms face challenges in solving MaOPs, leading to the proposal of a new fractional dominance relation and an improved objective space decomposition strategy. Experimental evaluations demonstrate that FDEA-I and FDEA-II significantly outperform six comparative algorithms.

SWARM AND EVOLUTIONARY COMPUTATION (2021)

Article Computer Science, Information Systems

Non-dominated sorting on performance indicators for evolutionary many-objective optimization

Hao Wang et al.

Summary: This study proposes a new multi-objective optimization method that converts multi-objective problems into bi-objective ones by using two performance indicators and non-dominated sorting to address engineering problems with multiple conflicting objectives. The method improves performance by balancing individual performance in different parts of the objective space and measuring diversity of each individual. Experimental results show competitiveness of the proposed method in solving problems with a large number of objectives.

INFORMATION SCIENCES (2021)

Article Computer Science, Information Systems

An adaptive Bayesian approach to surrogate-assisted evolutionary multi-objective optimization

Xilu Wang et al.

INFORMATION SCIENCES (2020)

Article Multidisciplinary Sciences

Residual Series Representation Algorithm for Solving Fuzzy Duffing Oscillator Equations

Mohammad Alshammari et al.

SYMMETRY-BASEL (2020)

Article Automation & Control Systems

Hyperplane Assisted Evolutionary Algorithm for Many-Objective Optimization Problems

Huangke Chen et al.

IEEE TRANSACTIONS ON CYBERNETICS (2020)

Article Computer Science, Artificial Intelligence

IGD Indicator-Based Evolutionary Algorithm for Many-Objective Optimization Problems

Yanan Sun et al.

IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION (2019)

Article Computer Science, Artificial Intelligence

A Classification-Based Surrogate-Assisted Evolutionary Algorithm for Expensive Many-Objective Optimization

Linqiang Pan et al.

IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION (2019)

Article Automation & Control Systems

Heterogeneous Ensemble-Based Infill Criterion for Evolutionary Multiobjective Optimization of Expensive Problems

Dan Guo et al.

IEEE TRANSACTIONS ON CYBERNETICS (2019)

Article Computer Science, Artificial Intelligence

Switching ripple suppressor design of the grid-connected inverters: A perspective of many-objective optimization with constraints handling

Zhixiong Zhang et al.

SWARM AND EVOLUTIONARY COMPUTATION (2019)

Article Computer Science, Artificial Intelligence

A Surrogate-Assisted Reference Vector Guided Evolutionary Algorithm for Computationally Expensive Many-Objective Optimization

Tinkle Chugh et al.

IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION (2018)

Article Computer Science, Information Systems

Ensemble of differential evolution variants

Guohua Wu et al.

INFORMATION SCIENCES (2018)

Article Computer Science, Artificial Intelligence

Adaptation of reproducing kernel algorithm for solving fuzzy Fredholm-Volterra integrodifferential equations

Omar Abu Arqub

NEURAL COMPUTING & APPLICATIONS (2017)

Editorial Material Computer Science, Artificial Intelligence

PlatEMO: A MATLAB Platform for Evolutionary Multi-Objective Optimization

Ye Tian et al.

IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE (2017)

Article Computer Science, Artificial Intelligence

A benchmark test suite for evolutionary many-objective optimization

Ran Cheng et al.

COMPLEX & INTELLIGENT SYSTEMS (2017)

Article Computer Science, Artificial Intelligence

A Reference Vector Guided Evolutionary Algorithm for Many-Objective Optimization

Ran Cheng et al.

IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION (2016)

Article Computer Science, Artificial Intelligence

Generalization of Pareto-Optimality for Many-Objective Evolutionary Optimization

Chenwen Zhu et al.

IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION (2016)

Article Computer Science, Interdisciplinary Applications

Bus Dwell Time Modeling Using Gene Expression Programming

Soroush Rashidi et al.

COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING (2015)

Article Computer Science, Artificial Intelligence

Fuzzy-Based Pareto Optimality for Many-Objective Evolutionary Algorithms

Zhenan He et al.

IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION (2014)

Article Computer Science, Artificial Intelligence

Approximation quality of the hypervolume indicator

Karl Bringmann et al.

ARTIFICIAL INTELLIGENCE (2013)

Article Computer Science, Artificial Intelligence

A Grid-Based Evolutionary Algorithm for Many-Objective Optimization

Shengxiang Yang et al.

IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION (2013)

Article Computer Science, Hardware & Architecture

Classification- and Regression-Assisted Differential Evolution for Computationally Expensive Problems

Xiao-Fen Lu et al.

JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY (2012)

Article Computer Science, Artificial Intelligence

HypE: An Algorithm for Fast Hypervolume-Based Many-Objective Optimization

Johannes Bader et al.

EVOLUTIONARY COMPUTATION (2011)

Article Computer Science, Artificial Intelligence

Generalizing Surrogate-Assisted Evolutionary Computation

Dudy Lim et al.

IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION (2010)

Article Computer Science, Artificial Intelligence

Expensive Multiobjective Optimization by MOEA/D With Gaussian Process Model

Qingfu Zhang et al.

IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION (2010)

Article Computer Science, Artificial Intelligence

A Systems Approach to Evolutionary Multiobjective Structural Optimization and Beyond

Yaochu Jin et al.

IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE (2009)

Article Computer Science, Artificial Intelligence

MOEA/D: A multiobjective evolutionary algorithm based on decomposition

Qingfu Zhang et al.

IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION (2007)

Article Management

SMS-EMOA: Multiobjective selection based on dominated hypervolume

Nicola Beume et al.

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH (2007)

Article Computer Science, Artificial Intelligence

ParEGO: A hybrid algorithm with on-line landscape approximation for expensive multiobjective optimization problems

J Knowles

IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION (2006)

Review Computer Science, Artificial Intelligence

Performance assessment of multiobjective optimizers: An analysis and review

E Zitzler et al.

IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION (2003)

Article Computer Science, Artificial Intelligence

A fast and elitist multiobjective genetic algorithm: NSGA-II

K Deb et al.

IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION (2002)