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Transformer Surrogate Genetic Programming for Dynamic Container Port Truck Dispatching
In the wake of burgeoning demands on port logistics, optimizing the operational efficiency of container ports has become a compelling necessity. A...
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Dimensionality Reduction in Surrogate Modeling: A Review of Combined Methods
Surrogate modeling has been popularized as an alternative to full-scale models in complex engineering processes such as manufacturing and...
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Physics-Informed Neural Network Surrogate Modeling Approach of Active/Passive Flow Control for Drag Reduction
This paper presents a novel surrogate modeling method with physics constraints that is specifically designed for optimal design in flow control...
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An Exploitation-Enhanced Bayesian Optimization Algorithm for High-Dimensional Expensive Problems
The Bayesian optimization (BO) algorithm is widely used to solve expensive optimization problems. However, when dealing with high-dimensional...
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Expedited Machine-Learning-Based Global Design Optimization of Antenna Systems Using Response Features and Multi-fidelity EM Analysis
The design of antenna systems poses a significant challenge due to stringent performance requirements dictated by contemporary applications and the...
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Can (and Should) Automated Surrogate Modelling Be Used for Simulation Assistance?
Recent advances in machine learning may be leveraged by researchers in the context of agent-based modelling. With the help of surrogate models,...
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Optimisation of a Chemical Process by Using Machine Learning Algorithms with Surrogate Modeling
Process models are getting more detailed, thus computational costs are rising. For this reason, the main aim of process engineering is to provide...
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Foundational Studies on ML-Based Enhancements
Many efficient evolutionary multi- and many-objective optimization algorithms, jointly referred to as EMâOAs, have been proposed in the last three...
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A Fitness Approximation Assisted Hyper-heuristic for the Permutation Flowshop Problem
Hyper-heuristics can be applied to solve complex optimization problems. Recently, an efficient hyper-heuristic (HHGA) was proposed for solving the...
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Key Issues in Real-World Applications of Many-Objective Optimisation and Decision Analysis
The insights and benefits to be realised through the optimisation of multiple independent, but conflicting objectives are well recognised by...
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A Distributed RBF-Assisted Differential Evolution for Distributed Expensive Constrained Optimization
With the development of Internet of things and distributed computing techniques, distributed and expensive constrained optimization problems (DECOPs)...
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An Evolutionary Approach for Scheduling a Fleet of Shared Electric Vehicles
In the present paper, we investigate the management of a fleet of electric vehicles. We propose a hybrid evolutionary approach for solving the...
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Evolutionary Machine Learning and Games
Evolutionary machine learning (EML) has been applied to games in multiple ways, and for multiple different purposes. Importantly, AI research in...
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Use of a Surrogate Model for Symbolic Discretization of Temporal Data Sets Through eMODiTS and a Training Set with Varying-Sized Instances
Time series classification is a supervised task in the field of temporal data mining. Time series naturally tend to be highly dimensional, requiring...
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Heterogeneous Objectives: State-of-the-Art and Future Research
Multiobjective optimization problems with heterogeneous objectives are defined as those that possess significantly different types of objective...
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Parallel Problem Solving from Nature – PPSN XVI 16th International Conference, PPSN 2020, Leiden, The Netherlands, September 5-9, 2020, Proceedings, Part I
This two-volume set LNCS 12269 and LNCS 12270 constitutes the refereed proceedings of the 16th International Conference on Parallel Problem Solving...
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BHO-MA: Bayesian Hyperparameter Optimization with Multi-objective Acquisition
Good hyperparameter values are crucial for the performance of machine learning models. In particular, poorly chosen values can cause under- or...
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Parallel Problem Solving from Nature – PPSN XVI 16th International Conference, PPSN 2020, Leiden, The Netherlands, September 5-9, 2020, Proceedings, Part II
This two-volume set LNCS 12269 and LNCS 12270 constitutes the refereed proceedings of the 16th International Conference on Parallel Problem Solving...
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Design of a Surrogate Model Assisted (1 + 1)-ES
Surrogate models are employed in evolutionary algorithms to replace expensive objective function evaluations with cheaper though usually inaccurate...
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Mechatronic Design Automation: A Short Review
This paper gives a short review on mechatronic design automation (MDA) whose optimization method is mainly based on evolutionary computation...