Search Results - (( variable objective scheduling algorithm ) OR ( java application learning algorithm ))
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A hybrid heuristic of variable neighbourhood descent and great deluge algorithm for efficient task scheduling in grid computing
Published 2019“…In this paper, we propose a novel hybrid heuristic-based algorithm, which synergised the excellent diversification capability of Great Deluge (GD) algorithm with the powerful systematic multi-neighbourhood search strategy captured in Variable Neighbourhood Descent (VND) algorithm, to efficiently schedule independent tasks in Grid computing environment with an objective of minimising the makespan. …”
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The use of heuristic ordering and particle swarm optimization for nurse scheduling problem
Published 2017“…The comparison of the result of HOPSO, harmony search algorithm (HSA) and heuristic variable neighborhood search (HVNS) is presented. …”
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Hybrid dynamic scheduling model for flexible manufacturing system with machine availability and new job arrivals
Published 2015“…The performance of the schedules as produced by the scheduling/rescheduling algorithms were investigated and compared. …”
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Improving resource management with multi-instance broker scheduling algorithm in hierarchical grid computing
Published 2016“…Multi-Instance Broker Scheduling Algorithm (MiBSA) has been proposed as a new scheduling algorithm to get rid of the drawback from the iHLBA algorithm. …”
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Optimization of Upstream Offshore Oilfield Production Planning under Uncertainty and Downstream Crude Oil Scheduling at Refinery Front-End
Published 2012“…The solution obtained from the LB–MILP model, i.e., the decision variables (binary variables), was used to obtain a feasible solution for model UB–NLP. …”
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Final Year Project -
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Optimization of Upstream Offshore Oilfield Production Planning under Uncertainty and Downstream Crude Oil Scheduling at Refinery Front-End
Published 2009“…The solution obtained from the LB-MILP model, i.e., the decision variables (binary variables), was used to obtain a feasible solution for model UB-NLP. …”
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Optimization Algorithms: A Comparison Study for Scheduling Problem at UIN Raden Fatah's Sharia and Law Faculty
Published 2024“…The research encompasses a systematic approach, beginning with a clear definition of constraints and objectives, followed by designing and implementing both algorithms to address the scheduling issues at the Faculty of Sharia and Law. …”
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Variable Neighborhood Descent and Whale Optimization Algorithm for Examination Timetabling Problems at Universiti Malaysia Sarawak
Published 2025“…A constructive algorithm was developed to generate an initial feasible solution, which was subsequently refined using two primary approaches to evaluate their efficiency: Iterative Threshold Pipe Variable Neighborhood Descent (IT-PVND), and a modified Whale Optimization Algorithm (WOA). …”
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An Educational Tool Aimed at Learning Metaheuristics
Published 2020“…In this paper, we introduce an education tool for learning metaheuristic algorithms that allows displaying the convergence speed of the corresponding metaheuristic upon setting/changing the dependable parameters. …”
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A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment
Published 2013“…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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Optimizing the placement of fire department in Kulim using greedy heuristic and simplex method / Muhammad Abu Syah Mohd Suzaly
Published 2023“…BIP is used to solve a wide range of problems, such as resource allocation, scheduling, and network design. The objective of this project is to determine the best location for the fire department that gives the maximum coverage of safety, to minimize the total number of fire department by using greedy heuristic algorithm and simplex method and compared both method that gives the best solution for optimization. …”
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OPTIMIZATION OF TWO FISH ENCRYPTION ALGORITHM ON FPGA
Published 2004“…There is also Reed-Solomon code with the MDS property used in the key schedule; this doesn't add diffusion to the cipher but does add diffusion to the key schedule.) …”
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Final Year Project -
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…This thesis is based on the application of sentiment classification algorithm to tweet data with the goal of classifying messages based on the polarity of sentiment towards a particular topic (or subject matter). …”
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Optimal operation and control of hybrid power systems with stochastic renewables and FACTS devices: An intelligent multi-objective optimization approach
Published 2025“…Employing both single- and multi-objective optimization algorithms, the research addresses the OPF problem in a modified IEEE-30 bus system through various case studies. …”
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Optimization Of Twofish Encryption Algorithm On FPGA
Published 2005“…There is also Reed-Solomon code with the MDS property used in the key schedule; this doesn't add diffusion to the cipher but does add diffusion to the key schedule.) …”
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Short-term electricity price forecasting in deregulated electricity market based on enhanced artificial intelligence techniques / Alireza Pourdaryaei
Published 2020“…The proposed feature selection technique comprises of Multi-objective Binary-valued Backtracking Search Algorithm (MOBBSA). …”
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Development of optimized maintenance scheduling model for coal-fired power plant boiler
Published 2023“…Generally, optimization computational and mathematical methods are designed for finding the best solution of a certain problems that aiming for minimizing or maximizing the objective functions based on the variables and subject to a set of constraints. …”
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