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Prediction and optimization of performance measures in electrical discharge machining using rapid prototy** tool electrodes
In this work, the performance of rapid prototy** (RP) based rapid tool is investigated during electrical discharge machining (EDM) of titanium as...
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Controlled showering optimization algorithm: an intelligent tool for decision making in global optimization
In this study a novel population based meta-heuristic, called controlled showering optimization (CSO) algorithm, for global optimization of...
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Industry 4.0: contributions of holonic manufacturing control architectures and future challenges
The flexibility claimed by the next generation production systems induces a deep modification of the behaviour and the core itself of the control...
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Stochastic Search in Metaheuristics
Stochastic search is a key mechanism underlying many metaheuristics. The chapter starts with the presentation of a general framework algorithm in the...
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Optimal Volt/Var Control Applied to Modern Distribution Systems
The voltage regulation in distribution systems refers to the primary objective of maintaining customers’ voltages within an acceptable range under...
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Designing energy-efficient high-precision multi-pass turning processes via robust optimization and artificial intelligence
This paper suggests a novel robust formulation designed for optimizing the parameters of the turning process in an uncertain environment for the...
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Recurrent feature-incorporated convolutional neural network for virtual metrology of the chemical mechanical planarization process
In semiconductor manufacturing, the chemical mechanical planarization (CMP) process produces higher thickness variability in the edge area of the...
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An oracle penalty and modified augmented Lagrangian methods with firefly algorithm for constrained optimization problems
Almost all engineering optimization problems in the real world are constrained in nature. Swarm intelligence is a bio-inspired technique based on...
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An Accelerated Introduction to Memetic Algorithms
Memetic algorithms (MAs) are optimization techniques based on the orchestrated interplay between global and local search components and have the...
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Optimizing a unit commitment problem using an evolutionary algorithm and a plurality of priority lists
The Unit Commitment Problem (UCP) is an operational research problem commonly encountered in energy management. It refers to the optimum scheduling...
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Radio resource management with QoS guarantees for LTE-A systems: a review focused on employing the multi-objective optimization techniques
The increasing number of subscribers’ demand has led to the evolution of future wireless networks that support multimedia applications and require...
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A restructured artificial bee colony optimizer combining life-cycle, local search and crossover operations for droplet property prediction in printable electronics fabrication
For printable electronics fabrication, a major challenge is the print resolution and accuracy delivered by a drop-on-demand piezoelectric inkjet...
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Combining metaheuristics with mathematical programming, constraint programming and machine learning
During the last years, interest on hybrid metaheuristics has risen considerably in the field of optimization and machine learning. The best results...
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Simulation optimization: a review of algorithms and applications
Simulation optimization (SO) refers to the optimization of an objective function subject to constraints, both of which can be evaluated through a...
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Swarm Intelligence
The complex and often coordinated behavior of swarms fascinates not only biologists but also computer scientists. Bird flocking and fish schooling...
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Using multi-objective evolutionary algorithms for single-objective constrained and unconstrained optimization
In recent decades, several multi-objective evolutionary algorithms have been successfully applied to a wide variety of multi-objective optimization...
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Simulation optimization: a review of algorithms and applications
Simulation optimization refers to the optimization of an objective function subject to constraints, both of which can be evaluated through a...
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PSO based time series models applied in exchange rate forecasting for business performance management
This research used the PSO algorithm to develop three new models, PSOGARCH, PSOEGARCH, and PSOGJR-GARCH, for improving business performance...
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A differential evolution algorithm for the capacitated VRP with flexibility of mixing pickup and delivery services and the maximum duration of a route in poultry industry
In this paper, we propose two heuristics to solve the General Q-Delivery Vehicle Routing Problem with consideration of flexibility of mixing pickup,...
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Combining metaheuristics with mathematical programming, constraint programming and machine learning
During the last years, interest on hybrid metaheuristics has risen considerably in the field of optimization and machine learning. The best results...
