Search Results - (( global optimization system algorithm ) OR ( sequence optimization method algorithm ))
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Global Algorithms for Nonlinear Discrete Optimization and Discrete-Valued Optimal Control Problems
Published 2009“…One of the more recent global optimization tools in the area of discrete optimization is known as the discrete filled function method. …”
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Performance optimization of simultaneous machine and automated guided vehicle scheduling using fuzzy logic controller based genetic algorithm.
Published 2012“…Integrated scheduling ofAGVs and machines is an essential factor contributing to the efficiency of the manufacturing system inFMS environment. Previously, genetic algorithm (GA) is considered as a heuristic method to solve AGVscheduling problem. …”
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Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems
Published 2019“…Previously, SED algorithm has been applied in to control scheme of wind farm to optimize the total power production but has yet to be applied in PID tuning. …”
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Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems
Published 2019“…Previously, SED algorithm has been applied in to control scheme of wind farm to optimize the total power production but has yet to be applied in PID tuning. …”
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Vector evaluated particle swarm optimization approach to solve assembly sequence planning problem
Published 2022“…Production scheduling is a complex combined optimization problem and the optimization method of which is not perfect [1]. …”
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Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures
Published 2020“…Any optimization algorithm is suitable for only a specific domain of optimization problems. …”
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Detection of Workers’ Behaviour in the Manufacturing Plant using Deep Learning
Published 2023“…Utilizing machine learning algorithms, our system learns and detects intricate activities from worker behavior sequences, offering a sophisticated analysis of worker efficiency. …”
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Application of genetic algorithm methods to optimize flowshop sequencing problem
Published 2008“…Application of genetic algorithm method to optimize flow shop sequencing problem as the title of this project is the study about the method used in order to optimize flow shop sequencing problem. …”
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Undergraduates Project Papers -
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MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD
Published 2023“…Thus, in this study, an optimization of the sequence operation in machining was conducted using an Artificial Intelligence method, which is the Ant Colony algorithm. …”
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MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD
Published 2023“…Thus, in this study, an optimization of the sequence operation in machining was conducted using an Artificial Intelligence method, which is the Ant Colony algorithm. …”
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MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD
Published 2023“…Thus, in this study, an optimization of the sequence operation in machining was conducted using an Artificial Intelligence method, which is the Ant Colony algorithm. …”
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MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD
Published 2023“…Thus, in this study, an optimization of the sequence operation in machining was conducted using an Artificial Intelligence method, which is the Ant Colony algorithm. …”
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Minimization of machining process sequence based on ant colony algorithm and conventional method
Published 2023“…Thus, in this study, an optimization of the sequence operation in machining was conducted using an Artificial Intelligence method, which is the Ant Colony algorithm. …”
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MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD
Published 2023“…Thus, in this study, an optimization of the sequence operation in machining was conducted using an Artificial Intelligence method, which is the Ant Colony algorithm. …”
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MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD
Published 2023“…Thus, in this study, an optimization of the sequence operation in machining was conducted using an Artificial Intelligence method, which is the Ant Colony algorithm. …”
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MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD
Published 2023“…Thus, in this study, an optimization of the sequence operation in machining was conducted using an Artificial Intelligence method, which is the Ant Colony algorithm. …”
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Product assembly sequence optimization based on genetic algorithm
Published 2010“…A single objective GA is used to obtain the optimal assembly sequence, exhibiting the minimum time taken. …”
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Product assembly and disassembly sequence optimization based on genetic algorithm and design for assembly methodologies
Published 2009“…In this paper, an Artificial Intelligence (AI) technique, namely Genetic Algorithm (GA) is proposed to optimize product components assembly and disassembly sequences.The proposed methodology is developed and tested on an industrial product made of plastics with no integrated assembly and permanent joint parts.GA method is applied to determine the accuracy and optimum results based on 20 assembly and disassembly sequence solutions that was generated by the Design for Assembly methodology.The results indicated that GA based approach is able to obtain a near optimal solution for assembly and disassembly sequences.…”
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Conference or Workshop Item -
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Comparative Analysis of Low Discrepancy Sequence-Based Initialization Approaches Using Population-Based Algorithms for Solving the Global Optimization Problems
Published 2021“…These algorithms can influence the convergence to find an efficient optimal solution. …”
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Performance comparison between genetic algorithm and ant colony optimization algorithm for mobile robot path planning in global static environment / Nohaidda Sariff
Published 2011“…The objective is to verify and compare the effectiveness of both algorithms in finding the optimal robot path in different types of global map environments. …”
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