Search Results - (( sequence optimization means algorithm ) OR ( using codification mining algorithm ))
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An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP
Published 2021“…To evaluate the proposed algorithm, the solutions to the TSP problem obtained from the proposed algorithm and swap sequence based PSO are compared in terms of the best solution, mean solution, and time taken to converge to the optimal solution. …”
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Modified Harris Hawks Optimization Algorithm For Protein Multiple Sequence Alignment
Published 2024“…A notable entrant in this domain is the harris hawks optimization (hho) algorithm, which has distinguished itself through published optimization outcomes, positioning it as a formidable competitor among state-of-the-art metaheuristics. …”
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3
Energy efficient modeling and optimization for assembly sequence planning using moth flame optimization
Published 2019“…The problem was then optimized using moth flame optimization (MFO) and compared with well-established algorithms such as genetic algorithm (GA), particle swarm optimization (PSO) and ant colony optimization (ACO). …”
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Application of intelligence based genetic algorithm for job sequencing problem on parallel mixed-model assembly line
Published 2010“…Then, it started to find the best sequence of jobs for each line based on the generated population by heuristic algorithm. …”
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Biogeography based optimization (BBO) algorithm to minimise non-productive time during hole-making process
Published 2015“…The proposed approach tackles the sequencing problem when several holes must be drilled by means of different tools to reach their desired size. …”
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Effect of adopting different dispatching rules on the mean flow time in a two machine batch-shop problem
Published 2005“…Therefore, researchers concentrated on developing branch-and-bound or heuristic algorithms. Ali Allahverdi, 1998 obtained the optimal solutions for minimizing mean flow time in a two-machine flow shop with Sequence-independent set up times by using three heuristic algorithms. …”
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Flock optimization algorithm-based deep learning model for diabetic disease detection improvement
Published 2024“…The collected data is processed by a Gaussian filtering approach that eliminates irrelevant information, reducing the overfitting issues. Then flock optimization algorithm is applied to detect the sequence; this process is used to reduce the convergence and optimization problems. …”
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VLSI floor planning optimization using genetic algorithm and cross entropy method / Angeline Teoh Szu Fern
Published 2012“…Hence, VLSI floorplanning is important in IC design. Floorplanning optimization consists of representation and optimization algorithm. …”
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A neural network modal decomposition mechanism in predicting network traffic
Published 2023“…Specifically, the predictive accuracy indexes such as Mean Absolute Percentage Error (MAPE), Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE) can reach a lowest optimum value of 1.1410, 0.1758 and 0.2263, and the average training time is reduced by 25.25%, 23.87% and 41.36%, respectively. …”
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Genetic algortihm to solve pcb component placement modeled as travelling salesman problem
Published 2013“…At the end of the project, we will be able to see how genetic algorithm used to get optimize result for TSP.…”
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Undergraduates Project Papers -
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Optimization of Simultaneous Scheduling for Machines and Automated Guided Vehicles Using Fuzzy Genetic Algorithm
Published 2009“…The objective of proposed FGA method is to minimize the makespan, production completion time of all jobs that they are produced simultaneously. An optimal sequence of operations is obtained by GA. …”
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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“…Therefore, two meta-heuristic algorithms, namely genetic algorithm (GA) and simulated annealing (SA) algorithm, were developed to optimize the integrated scheduling of handling equipment. …”
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Modified firefly algorithm for directional overcurrent relay coordination in power system protection / Muhamad Hatta Hussain
Published 2020“…Thus, a reliable optimization technique such as Nature Inspired Metaheuristic Algorithms (NIMA) is crucial to address this issue. …”
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Hybrid multiobjective genetic algorithm for integrated dynamic scheduling and routing of jobs and automated guided vehicles in flexible manufacturing systems
Published 2014“…The algorithm generates an integrated scheduling and detail paths route while optimizing makespan, AGV travel time, mean flow time and penalty cost due to jobs tardiness and delay as a result of conflict avoidance. …”
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Antenna arrays in multi-user detection of spread spectrum signals
Published 2007“…A number of multi-user detection algorithms have been suggested by various authors. Optimal receivers based upon maximum likelihood sequence decoding are quite complex, their complexity increasing exponentially with the number of users in the system. …”
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Conference or Workshop Item -
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A genetic algorithm to minimise the maximum lateness on a single machine family scheduling problem
Published 2009“…In this study, we propose an Optimised Crossover Genetic Algorithm (OCGA) for the problem. The objective is to find a schedule which minimises the maximum lateness of the jobs in the presence of the sequence independent family setup times.In brief, the proposed OCGA uses binary representation to encode the problem. …”
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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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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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