4.7 Article

Multi-objective optimization of neural network with stochastic directed search

Related references

Note: Only part of the references are listed.
Article Thermodynamics

Multi-objective optimization of desiccant wheel via analytical model and genetic algorithm

Heng-Yi Li et al.

Summary: This research proposes an optimal design framework combining analytical model, multi-objective optimization, and decision-making for optimizing the dehumidification performance and energy consumption of a desiccant wheel. An overall heat and mass balance-based model is used to derive the objective functions and constraints for the desiccant wheel. The non-dominated sorting genetic algorithm II (NSGA-II) is employed to calculate the Pareto optimal front of the two-objective optimization, and the results are analyzed using a psychrometric chart. The final optimal solution is obtained using the technique for order preference by similarity to ideal solution (TOPSIS) based on four criteria, resulting in further improvements on the outlet process air humidity ratio and the dehumidification coefficient of performance when applied to an existing example.

APPLIED THERMAL ENGINEERING (2023)

Article Computer Science, Artificial Intelligence

An improved learning automata based multi-objective whale optimization approach for multi-objective portfolio optimization in financial markets

Hakimeh Morteza et al.

Summary: This paper proposes a whale optimization-based multi-objective approach to optimize portfolios in financial markets. The approach utilizes multiple sub-populations, exchange of information between them, parameter control, and the creation of a non-dominated solutions archive to enhance accuracy, diversity, and convergence speed.

EXPERT SYSTEMS WITH APPLICATIONS (2023)

Article Energy & Fuels

Multi-objective optimization operation of micro energy network with energy storage system based on improved weighted fuzzy method

Hong Qu et al.

Summary: This paper investigates the multi-objective optimization problem of micro energy networks. It first establishes an optimal operation model considering the factors of economy, energy, and environment, and then proposes an improved weighted fuzzy method, which is solved using the particle swarm algorithm. The results show that this method can improve the coordination among multiple objectives and the robustness of the algorithm.

ENERGY REPORTS (2023)

Article Computer Science, Artificial Intelligence

A novel portfolio optimization model via combining multi-objective optimization and multi-attribute decision making

Yongjie Zheng et al.

Summary: This paper presents a method that combines multi-objective optimization and multi-attribute decision-making to solve the portfolio optimization problem, successfully addressing the dual-objective portfolio optimization model. Through a case study and comparison with other algorithms, the competitiveness of the proposed algorithm is demonstrated.

APPLIED INTELLIGENCE (2022)

Proceedings Paper Computer Science, Cybernetics

Multi-objective Framework for Quantile Forecasting in Financial Time Series Using Transformers

Samuel Lopez-Ruiz et al.

Summary: This study emphasizes the importance of uncertainty in financial time series forecasting and optimizes the quality of quantile interval predictions using multi-objective evolutionary algorithms. The high performance quantile multi-horizon predictions are generated by an attention-based deep learning model based on transformers, and the weights are optimized using evolutionary algorithms. The results show a wide range of solutions that allow decision makers to efficiently fine-tune the quantile forecasts without retraining the neural network.

PROCEEDINGS OF THE 2022 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE (GECCO'22) (2022)

Article Computer Science, Information Systems

Multi-objective prediction intervals for wind power forecast based on deep neural networks

Min Zhou et al.

Summary: Wind power forecast plays a critical role in modern power systems, and this paper proposes a novel interval forecast model based on LSTM to construct prediction intervals effectively. An improved PI evaluation criterion and a multi-objective optimization framework are introduced to investigate the relationship between PI estimation error and average width. The proposed model and algorithm's effectiveness is demonstrated through experiments on real world wind power dataset.

INFORMATION SCIENCES (2021)

Article Computer Science, Artificial Intelligence

Utilizing dependence among variables in evolutionary algorithms for mixed-integer programming: A case study on multi-objective constrained portfolio optimization

Yi Chen et al.

Summary: This paper introduces a Compressed Coding Scheme (CCS) for solving multi-objective constrained portfolio optimization problems, which effectively utilizes the dependencies among variables. Experimental results demonstrate that CCS is efficient and robust for handling optimization problems with a large number of assets.

SWARM AND EVOLUTIONARY COMPUTATION (2021)

Article Economics

Temporal Fusion Transformers for interpretable multi-horizon time series forecasting

Bryan Lim et al.

Summary: This paper introduces the Temporal Fusion Transformer (TFT), a novel attention-based architecture that combines high-performance multi-horizon forecasting with interpretable insights into temporal dynamics. TFT utilizes recurrent layers for local processing and interpretable self-attention layers for long-term dependencies, achieving high performance in a wide range of scenarios. By selecting relevant features and suppressing unnecessary components, TFT demonstrates significant performance improvements over existing benchmarks on various real-world datasets.

INTERNATIONAL JOURNAL OF FORECASTING (2021)

Article Computer Science, Information Systems

A Surrogate-Assisted Many-Objective Evolutionary Algorithm Using Multi- Classification and Coevolution for Expensive Optimization Problems

Ruoyu Wang et al.

Summary: This paper proposes a surrogate-assisted many-objective evolutionary algorithm that utilizes the cooperation of multi-classification and regression models to improve search quality and reduce computational cost. It divides the population into classes using a multi-classification model for diversity, and utilizes distance and angle regression models for convergence and diversity in each class. Experimental results confirm its effectiveness on expensive test problems with up to 10 objectives.

IEEE ACCESS (2021)

Article Computer Science, Software Engineering

MOBOpt - multi-objective Bayesian optimization

Paulo Paneque Galuzio et al.

SOFTWAREX (2020)

Article Computer Science, Information Systems

Pymoo: Multi-Objective Optimization in Python

Julian Blank et al.

IEEE ACCESS (2020)

Article Operations Research & Management Science

Enhanced directed search: a continuation method for mixed-integer multi-objective optimization problems

Honggang Wang et al.

ANNALS OF OPERATIONS RESEARCH (2019)

Article Engineering, Multidisciplinary

Pareto Tracer: a predictor-corrector method for multi-objective optimization problems

Adanay Martin et al.

ENGINEERING OPTIMIZATION (2018)

Article Operations Research & Management Science

The directed search method for multi-objective memetic algorithms

Oliver Schuetze et al.

COMPUTATIONAL OPTIMIZATION AND APPLICATIONS (2016)

Article Green & Sustainable Science & Technology

A multiobjective framework for wind speed prediction interval forecasts

Nitin Anand Shrivastava et al.

RENEWABLE ENERGY (2016)

Article Computer Science, Artificial Intelligence

An Interval-Valued Neural Network Approach for Uncertainty Quantification in Short-Term Wind Speed Prediction

Ronay Ak et al.

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2015)

Article Computer Science, Artificial Intelligence

Particle swarm optimization for construction of neural network-based prediction intervals

Hao Quan et al.

NEUROCOMPUTING (2014)

Article Computer Science, Interdisciplinary Applications

Zigzag Search for Continuous Multiobjective Optimization

Honggang Wang

INFORMS JOURNAL ON COMPUTING (2013)

Article Mathematics

Multiple-gradient descent algorithm (MGDA) for multiobjective optimization

Jean-Antoine Desideri

COMPTES RENDUS MATHEMATIQUE (2012)

Article Computer Science, Artificial Intelligence

HCS: A New Local Search Strategy for Memetic Multiobjective Evolutionary Algorithms

Adriana Lara et al.

IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION (2010)

Article Computer Science, Interdisciplinary Applications

The weighted sum method for multi-objective optimization: new insights

R. Timothy Marler et al.

STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION (2010)

Article Mathematics, Applied

NEWTON'S METHOD FOR MULTIOBJECTIVE OPTIMIZATION

J. Fliege et al.

SIAM JOURNAL ON OPTIMIZATION (2009)

Article Operations Research & Management Science

Stochastic method for the solution of unconstrained vector optimization problems

S Schäffler et al.

JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS (2002)

Article Operations Research & Management Science

Steepest descent methods for multicriteria optimization

J Fliege et al.

MATHEMATICAL METHODS OF OPERATIONS RESEARCH (2000)