Search Results - (( using case method algorithm ) OR ( sequence optimization method algorithm ))
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1
Product assembly sequence optimization based on genetic algorithm
Published 2010“…The assembly experiment is done using a case study product and results were compared with manual assembly sequences using the ‘Design for Assembly’(DFA) method. …”
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Development of multi-objective optimization methods for integrated scheduling of handling equipment (AGVs, QCs, SP-AS/RS) in automated container terminals
Published 2012“…Results indicate that “earliest available vehicle” is the best heuristic rule for the integrated scheduling method. Moreover, it is shown that on average, the best objective values obtained by the GA and SA algorithm, are only 6.4% and 3.7% worse than the optimal ones found by the MIP model, respectively; demonstrating that both algorithms are able to achieve near optimal solutions. …”
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3
An assembly sequence planning approach with a rule-based multi-state gravitational search algorithm
Published 2015“…In this paper, an approach based on a new variant of the gravitational search algorithm (GSA) called the rule-based multi-state gravitational search algorithm (RBMSGSA) is used to solve the assembly sequence planning problem. …”
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An Assembly Sequence Planning Approach with a Rule-based Multi-state Gravitational Search Algorithm
Published 2015“…In this paper, an approach based on a new variant of the gravitational search algorithm (GSA) called the rule-based multi-state gravitational search algorithm (RBMSGSA) is used to solve the assembly sequence planning problem. …”
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5
T-way strategy for sequence input interactions test case generation adopting fish swarm algorithm
Published 2019“…In order to reduce test cases several T-way sequence input interaction strategies are explored, such as, Bee Algorithm(BA), Kuhn encoding (K) , ASP with Clasp , CP with Sugar, Erdem (ER) exact encoding, Tarui (TA) Method, U, UR, D and DR, Brain (BR). …”
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Conference or Workshop Item -
6
Natural gas liquid (NGL) distillation process using driving force and thermal pinch analysis methods: Energy and economic assessment / Munawar Zaman Shahruddin ... [et al.]
Published 2020“…This research proposes the methodology to determine the optimal sequence of distillation columns by using driving force method. …”
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Optimization of Simultaneous Scheduling for Machines and Automated Guided Vehicles Using Fuzzy Genetic Algorithm
Published 2009“…An optimal sequence of operations is obtained by GA. …”
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8
Optimisation of multi-stage production-inspection stations using genetic algorithm
Published 2000“…The optimal allocation and sequencing of inspection stations is to be presented in this paper. …”
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Network reconfiguration and DG sizing incorporating optimal switching sequence for system improvement / Ola Subhi Waheed Badran
Published 2018“…These values were much lower compared to any other random case. Furthermore, the optimal sequence keeps the buses voltages within allowable limit during the switching process. …”
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10
A genetic algorithm to minimise the maximum lateness on a single machine family scheduling problem
Published 2009“…The OCGA is compared with other well known local search method namely dynamic length tabu search, randomised steepest descent method, and other variants of genetic algorithms using extensive data sets collected from the literatures. …”
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11
Kernerlized Correlation Filters Parameters Optimization For Enhanced Visual Tracking
Published 2017“…Thus, the proposed method had increased the accuracy and robustness of the visual tracking on many of the video sequences.…”
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Monograph -
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Training size optimization with reduced complexity in cell-free massive MIMO system
Published 2019“…In addition, we proposed and compared the performance of different training size optimization algorithms, namely exhaustive search optimization, bisection optimization and min–max optimization, with each method has different level of calculation complexities. …”
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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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Energy-Efficient Low-Complexity Algorithm in 5G Massive MIMO Systems
Published 2021“…This formulates the optimization problem of joint optimal antenna selection, transmits power allocation and joint user selection to mitigate inter-cellinterference in downlink multi-cell massiveMIMO systems under minimized reuse of pilot sequences based on a novel iterative low-complexity algorithm (LCA) for Newton’s methods and Lagrange multipliers. …”
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Optimal Maintenance Scheduling for Multi-Component E-Manufacturing System
Published 2009“…The results demonstrate that the proposed optimal maintenance scheduling method yields much better system value rather than sequencing methods. …”
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Estimation of Transformers Health Index Based on Condition Parameter Factor and Hidden Markov Model
Published 2023Conference Paper -
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Weather Prediction for Strawberry Cultivation Using Double Exponential Smoothing and Golden Section Optimization Methods
Published 2024“…The system was developed by implementing the PHP programming language on the interface design as well as MySQL as a database processing. The algorithm used to predict the air temperature feature, wind speed feature, and rainfall feature was Double Exponential Smoothing, followed by the optimization of the Golden Section method to select the right smoothing value. …”
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Comparative Analysis Using Bayesian Approach To Neural Network Of Translational Initiation Sites In Alternative Polymorphic Contex
Published 2012“…The objectives of this paper are to develop useful algorithms and to build a new classification model for the case study.The first approach of neural network includes training on algorithms of Resilient Backpropagation,Scaled Conjugate Gradient Backpropagation and Levenberg-Marquardt.The outputs are used in comparison with Bayesian Neural Network for efficiency comparison.The results showed that Resilient Backpropagation have the consistency in all measurement but performs less in accuracy.In second approach,the Bayesian Classifier_01 outperforms the Resilient Backpropagation by successfully increasing the overall prediction accuracy by 16.0%.The Bayesian Classifier_02 is built to improve the accuracy by adding new features of chemical properties as selected by the Information Gain Ratio method,and increasing the length of the window sequence to 201.The result shows that the built model successfully increases the accuracy by 96.0%.In comparison,the Bayesian model outperforms Tikole and Sankararamakrishnan (2008) by increasing the sensitivity by 10% and specificity by 26%. …”
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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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