An Improved Strength Pareto Evolutionary Algorithm 2 for Constrained Multiobjective Optimization Problems in Continuous Annealing Furnace
Sign Up to like & getrecommendations! Published in 2025 at "steel research international"
DOI: 10.1002/srin.202500923
Abstract: This research proposes a constraint multiobjective optimization algorithm that combines the auxiliary task method with the strength Pareto evolutionary algorithm 2 (ATM‐SPEA2). The algorithm is designed to optimize the heating process in the continuous annealing… read more here.
Keywords: constrained multiobjective; algorithm; strength pareto; multiobjective optimization ... See more keywords
Integration of storage systems in distribution networks through multiobjective optimization
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DOI: 10.1007/s00202-017-0672-6
Abstract: The use of storage systems in distribution networks allows smoothing the load diagram. In fact, the cost of energy is different along the day and companies can be encouraged to use these systems, since the… read more here.
Keywords: systems distribution; storage; multiobjective optimization; storage systems ... See more keywords
Robust multiobjective optimization with application to Internet routing
Sign Up to like & getrecommendations! Published in 2018 at "Annals of Operations Research"
DOI: 10.1007/s10479-017-2751-5
Abstract: Robust optimization addressing decision making under uncertainty has been very well developed for problems with a single objective function and applied to areas of human activity such as portfolio selection, investment decisions, signal processing, and… read more here.
Keywords: uncertainty; application; robust multiobjective; optimization ... See more keywords
An implicit filtering algorithm for derivative-free multiobjective optimization with box constraints
Sign Up to like & getrecommendations! Published in 2018 at "Computational Optimization and Applications"
DOI: 10.1007/s10589-017-9953-2
Abstract: This paper is concerned with the definition of new derivative-free methods for box constrained multiobjective optimization. The method that we propose is a non-trivial extension of the well-known implicit filtering algorithm to the multiobjective case.… read more here.
Keywords: implicit filtering; derivative free; filtering algorithm; box ... See more keywords
Bundle-based descent method for nonsmooth multiobjective DC optimization with inequality constraints
Sign Up to like & getrecommendations! Published in 2018 at "Journal of Global Optimization"
DOI: 10.1007/s10898-018-0651-0
Abstract: Multiobjective DC optimization problems arise naturally, for example, in data classification and cluster analysis playing a crucial role in data mining. In this paper, we propose a new multiobjective double bundle method designed for nonsmooth… read more here.
Keywords: based descent; method; bundle based; optimization ... See more keywords
A surrogate-assisted a priori multiobjective evolutionary algorithm for constrained multiobjective optimization problems
Sign Up to like & getrecommendations! Published in 2024 at "Journal of Global Optimization"
DOI: 10.1007/s10898-024-01387-z
Abstract: We consider multiobjective optimization problems with at least one computationally expensive constraint function and propose a novel surrogate-assisted evolutionary algorithm that can incorporate preference information given a priori. We employ Kriging models to approximate expensive… read more here.
Keywords: optimization problems; evolutionary algorithm; optimization; multiobjective optimization ... See more keywords
A proximal bundle-based algorithm for nonsmooth constrained multiobjective optimization problems with inexact data
Sign Up to like & getrecommendations! Published in 2021 at "Numerical Algorithms"
DOI: 10.1007/s11075-021-01128-3
Abstract: In this paper, a proximal bundle-based method for solving nonsmooth nonconvex constrained multiobjective optimization problems with inexact information is proposed and analyzed. In this method, each objective function is treated individually without employing any scalarization.… read more here.
Keywords: proximal; proximal bundle; bundle based; multiobjective optimization ... See more keywords
A prediction method based on fractional order displacement for dynamic multiobjective optimization.
Sign Up to like & getrecommendations! Published in 2022 at "ISA transactions"
DOI: 10.1016/j.isatra.2022.03.015
Abstract: Prediction-based methods have become more popular for solving dynamic multiobjective optimization problems. However, most of these proposed methods only use the optimal solutions in the previous two or three environments to predict the new optimal… read more here.
Keywords: multiobjective optimization; prediction method; method; optimal solutions ... See more keywords
Potential of interactive multiobjective optimization in supporting the design of a groundwater biodenitrification process.
Sign Up to like & getrecommendations! Published in 2019 at "Journal of environmental management"
DOI: 10.1016/j.jenvman.2019.109770
Abstract: The design of water treatment plants requires simultaneous analysis of technical, economic and environmental aspects, identified by multiple conflicting objectives. We demonstrated the advantages of an interactive multiobjective optimization (MOO) method over a posteriori methods… read more here.
Keywords: process; potential interactive; interactive multiobjective; multiobjective optimization ... See more keywords
Optimal Solvent Design for Extractive Distillation Processes: A Multiobjective Optimization-Based Hierarchical Framework
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DOI: 10.1021/acs.iecr.8b04245
Abstract: Extractive distillation is a widely accepted and commercialized process for separating azeotropic mixtures compared to conventional distillation. The search for high-performing solvents, or entrainers, needed in extractive distillation is a challenging task. The heuristic guideline… read more here.
Keywords: extractive distillation; optimization based; framework; distillation ... See more keywords
Structural Coarse-Graining via Multiobjective Optimization with Differentiable Simulation.
Sign Up to like & getrecommendations! Published in 2024 at "Journal of chemical theory and computation"
DOI: 10.1021/acs.jctc.3c01348
Abstract: In the realm of multiscale molecular simulations, structure-based coarse-graining is a prominent approach for creating efficient coarse-grained (CG) representations of soft matter systems, such as polymers. This involves optimizing CG interactions by matching static correlation… read more here.
Keywords: optimization differentiable; coarse graining; optimization; multiobjective optimization ... See more keywords