Recent advances in Bayesian optimization
Bayesian optimization has emerged at the forefront of expensive black-box optimization due
to its data efficiency. Recent years have witnessed a proliferation of studies on the …
to its data efficiency. Recent years have witnessed a proliferation of studies on the …
A comprehensive review on multi-objective optimization techniques: Past, present and future
Realistic problems typically have many conflicting objectives. Therefore, it is instinctive to
look at the engineering problems as multi-objective optimization problems. This paper briefly …
look at the engineering problems as multi-objective optimization problems. This paper briefly …
Multi-objective optimization of a hybrid renewable energy system supplying a residential building using NSGA-II and MOPSO algorithms
R Cheraghi, MH Jahangir - Energy Conversion and Management, 2023 - Elsevier
Multi-objective optimization of a hybrid system is investigated to supply an autonomous
residential building. The proposed system consists of photovoltaic panel, wind turbine …
residential building. The proposed system consists of photovoltaic panel, wind turbine …
A practical guide to multi-objective reinforcement learning and planning
Real-world sequential decision-making tasks are generally complex, requiring trade-offs
between multiple, often conflicting, objectives. Despite this, the majority of research in …
between multiple, often conflicting, objectives. Despite this, the majority of research in …
Multiclass feature selection with metaheuristic optimization algorithms: a review
Selecting relevant feature subsets is vital in machine learning, and multiclass feature
selection is harder to perform since most classifications are binary. The feature selection …
selection is harder to perform since most classifications are binary. The feature selection …
A Pareto-based hybrid iterated greedy algorithm for energy-efficient scheduling of distributed hybrid flowshop
C Lu, Q Liu, B Zhang, L Yin - Expert Systems with Applications, 2022 - Elsevier
Due to its practicality, hybrid flowshop scheduling problem (HFSP) with productivity objective
has been extensively explored. However, studies on HFSP considering green objective in …
has been extensively explored. However, studies on HFSP considering green objective in …
A review of multi-objective optimization: methods and algorithms in mechanical engineering problems
The optimization problems that must meet more than one objective are called multi-objective
optimization problems and may present several optimal solutions. This manuscript brings …
optimization problems and may present several optimal solutions. This manuscript brings …
An evolutionary multitasking optimization framework for constrained multiobjective optimization problems
When addressing constrained multiobjective optimization problems (CMOPs) via
evolutionary algorithms, various constraints and multiple objectives need to be satisfied and …
evolutionary algorithms, various constraints and multiple objectives need to be satisfied and …
A review of Pareto pruning methods for multi-objective optimization
Previous researchers have made impressive strides in develo** algorithms and solution
methodologies to address multi-objective optimization (MOO) problems in industrial …
methodologies to address multi-objective optimization (MOO) problems in industrial …
A hybrid robust-interval optimization approach for integrated energy systems planning under uncertainties
The presence of multiple uncertainties in demand response and renewable energy
generation significantly impeded the planning of integrated energy systems (IES). To …
generation significantly impeded the planning of integrated energy systems (IES). To …