Search Results - (( initial solution machine algorithm ) OR ( evolution optimization bat algorithm ))
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Multi-Swarm bat algorithm
Published 2023“…In this study a new Bat Algorithm (BA) based on multi-swarm technique called the Multi-Swarm Bat Algorithm (MSBA) is proposed to address the problem of premature convergence phenomenon. …”
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Quality of service and energy efficient aware (QEEA) scheduling algorithm for long term evolution (LTE) network / Nurulanis Mohd Yusoff
Published 2017“…Basically, the QEEA is based on the Time Domain (TD) and Frequency Domain (FD) scheduling where it is dependent on the QoS requirements to allocate resources. The proposed algorithm is compared against other scheduling algorithms, namely, the Channel and QoS Aware (CQA), Priority Set Scheduler (PSS), Proportional Fair (PF), Maximum Throughput (MT) and Blind Average Throughput (BAT). …”
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Flexible job shop scheduling using priority heuristics and genetic algorithm
Published 2010“…In the next method, a genetic algorithm has been developed. It has been shown that proposed genetic algorithm with a reinforced initial population (GA2) has better efficiency compared to a proposed genetic algorithm with fully random initial population (GA0). …”
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Hybrid dynamic scheduling model for flexible manufacturing system with machine availability and new job arrivals
Published 2015“…The BBO-VNS match-up algorithm manipulates the idle times on machines within the time horizon for assigning the affected operations by breakdown and/or newly arrived orders. …”
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Data Analysis and Machine Learning Algorithms Evaluation for Bioliq AI-based Predictive Tool
Published 2019“…The mass production hasn’t initiated due to the inefficiency of the process and the dependency on experts. …”
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A branch and bound and simulated annealing approach for job shop scheduling
Published 2004“…In the branch and bound approach, the job shop scheduling problem is represented by a disjunctive graph, then the optimal schedule is obtained using the branch and bound algorithm while simulated annealing is a local search based algorithm which will slightly perturb the initial feasible solution to decrease the makespan. …”
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A new variant of black hole algorithm based on multi population and levy flight for clustering problem
Published 2020“…Black Hole (BH) optimization algorithm has been underlined as a solution for data clustering problems. …”
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A comprehensive review of crop yield prediction using machine learning approaches with special emphasis on palm oil yield prediction
Published 2021“…Initially, the current status of palm oil yield around the world is presented, along with a brief discussion on the overview of widely used features and prediction algorithms. …”
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Improved whale optimization algorithm for feature selection in Arabic sentiment analysis
Published 2019“…The comprehensive experiments results show that the proposed algorithm outperforms all other algorithms in terms of sentiment analysis classification accuracy through finding the best solutions, while its also minimizes the number of selected features. © 2018, Springer Science+Business Media, LLC, part of Springer Nature.…”
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Multi-Objective Multi-Exemplar Particle Swarm Optimization Algorithm with Local Awareness
Published 2024“…Many machine learning algorithms excel at handling problems with conflicting objectives. …”
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Enhancement of feature sets for subjectivity analysis on Malay-English code-switching text
Published 2023“…The combination has consistently performed at the accuracy of 59% using both machine learning classifiers. The consistent performance indicates the combined feature sets are the viable solution for subjectivity analysis on the Malay-English code-switching text.…”
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Bottleneck-based heuristic for permutation flowshop scheduling
Published 2017“…The newly heuristic is developed by introducing the bottleneck-based concept that was applied at the beginning of initial solution determination. The heuristic is known as Bottleneck-Based (BNB) heuristic. …”
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Simulated Kalman Filter algorithms for solving optimization problems
Published 2019“…However, the HKA algorithm has its own flaws. Although it was introduced as a population-based stochastic optimization algorithm, HKA is not exactly a population-based algorithm because it initializes and updates only a single solution. …”
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An artificial bee colony-based double layered neural network approach for solving quadratic Bi-level programming problems
Published 2020“…For an efficient and effective solution of such problems, the proposed potential methodology includes an improved Artificial Bee Colony (ABC) algorithm, a Hopfield Network (HN), and a Boltzmann Machine (BM). …”
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Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm
Published 2025“…Parallel power loads anomalies are processed by a fast-density peak clustering technique that capitalizes on the hybrid strengths of Canopy and K-means algorithms all within Apache Mahout's distributed machine-learning environment. …”
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A Genetic Algorithm for the Real-world University Course Timetabling Problem
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A Hybrid of Ant Colony Optimization Algorithm and Simulated Annealing for Classification Rules
Published 2013“…Classification rule induction is one of the problems solved by the Ant-miner algorithm, a variant of ACO, which was initiated by Parpinelli in 2001. …”
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