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A simple and efficient real-coded genetic algorithm for constrained optimization
A novel and efficient RCGA for constrained optimization has been proposed.The proposed RCGA integrates three effective and novel evolutionary operators named RS, DBX and DRM.The proposed RCGA isExpand
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A real-coded genetic algorithm with a direction-based crossover operator
In this paper, we develop a parallel-structured real-coded genetic algorithm (RCGA), named the RGA-RDD, for numerical optimization. Technically, the proposed RGA-RDD integrates three speciallyExpand
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Black-box optimization benchmarking for noiseless function testbed using a direction-based RCGA
This paper benchmarks a novel and efficient real-coded genetic algorithm (RCGA) enhanced from our previous work [1] on the noisefree BBOB 2012 testbed. The enhanced algorithm termed asExpand
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Model-Assisted Control of Flow Front in Resin Transfer Molding Based on Real-Time Estimation of Permeability/Porosity Ratio
Resin transfer molding (RTM) is a popular manufacturing technique that produces fiber reinforced polymer (FRP) composites. In this paper, a model-assisted flow front control system is developed basedExpand
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An Intelligent Run-to-Run Control Strategy for Chemical–Mechanical Polishing Processes
This paper presents a novel intelligent run-to-run control strategy for chemical-mechanical polishing (CMP) processes. With the help of the recursive least squares identification method for modelExpand
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A study on real-coded genetic algorithm for process optimization using ranking selection, direction-based crossover and dynamic mutation
In this paper, a novel and efficient real-coded genetic algorithm (RCGA) for process optimization is developed. The proposed RCGA is equipped with Ranking Selection (RS), Direction-Based CrossoverExpand
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Mathematical modeling and optimal design of an MOCVD reactor for GaAs film growth
Abstract This paper considers the mathematical modeling and optimal design of a horizontal metal-organic chemical vapor deposition (MOCVD) reactor for GaAs film growth. A detailed 3D model of theExpand
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Transfer learning for efficient meta-modeling of process simulations
Abstract In chemical engineering applications, computational efficient meta-models have been successfully implemented in many instants to surrogate the high-fidelity computational fluid dynamicsExpand
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Physically Consistent Soft-Sensor Development Using Sequence-to-Sequence Neural Networks
Soft sensors attempt to predict the key quality variables that are infrequently available using the sensor and manipulated variables that are readily available. Since only limited amount of labeledExpand
A simple model‐based nonlinear control strategy for feedback linearizable nonlinear processes
Abstract In this paper we propose a simple and novel model‐based nonlinear control strategy for feedback linearizable nonlinear processes. The nonlinear controller, called NLC, has a forward staticExpand