Search Results - (( using modification scheduling algorithm ) OR ( evolution optimization _ algorithm ))
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Hybrid genetic algorithm with multi-parents recombination for job shop scheduling problems / Ong Chung Sin
Published 2013“…Job Shop Scheduling Problem (JSSP) is one of the well-known hard combinatorial scheduling problems and one of the most computationally difficult combinatorial optimization problems considered to date. …”
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A refined differential evolution algorithm for improving the performance of optimization process
Published 2011“…Various Artificial Intelligent (AI) algorithms can be applied in solving optimization problems. …”
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Graph coloring program of exam scheduling modeling based on bitwise coloring algorithm using python
Published 2022“…Graph coloring has a wide range of applications and is commonly used to solve scheduling issues. In this article, the researchers design an algorithm and apply it to a computer program (Python) to solve graph coloring and to visualize the variation of exam scheduling modeling at Binus University in graphs based on the Bitwise Graph Coloring Algorithm. …”
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Reducing Tasks Migration in LRE-TL Real-time Multiprocessor Scheduling Algorithm
Published 2013“…In this paper we present a modification of Local Remaining Execution (LRE-TL) real-time multiprocessor scheduling algorithm to reduce tasks migration significantly. …”
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5
Two level Differential Evolution algorithms for ARMA parameters estimatio
Published 2013“…The problem of determining simultaneously the model order and coefficient of an Autoregressive Moving Average (ARMA) model is examined in this paper. An Evolutionary Algorithm (EA) comprising two-level Differential Evolution (DE) optimization scheme is proposed. …”
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6
Comparison between Lamarckian Evolution and Baldwin Evolution of neural network
Published 2006“…We presented hybrid genetic algorithm for optimizing weights as well as the topology of artificial neural networks, by introducing the concepts of Lamarckian and Baldwin evolution effects. …”
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7
Harmony search algorithm for curriculum-based course timetabling problem
Published 2013“…With proper modification in terms of the approach in this algorithm would make the algorithm perform better on curriculum-based course timetabling.…”
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Harmony search algorithm for curriculum-based course timetabling problem
Published 2013“…However, the algorithm produced results that were not comparatively better than those previously known as best solution.With proper modification in terms of the approach in this algorithm would make the algorithm perform better on curriculum-based course timetabling.…”
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A hybrid genetic algorithm for optimization of scheduling workflow applications in heterogeneous computing systems
Published 2016“…The performance of the proposed algorithm is analyzed by using synthesized datasets, and real-world application workflows. …”
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Broadening selection competitive constraint handling algorithm for faster convergence
Published 2020“…In this study, the BSCCH algorithm has been coupled with Differential Evolution algorithm as a proof of concept because it is found to be an efficient algorithm in the literature for constrained optimization problems. …”
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Minimizing Scheduling Overhead In LRE-TL Real-Time Multiprocessor Scheduling Algorithm
Published 2015“…In this paper, we present a modification of Local Remaining Execution-Time and Local time domain (LRE-TL) real-time multiprocessor scheduling algorithm, aimed at reducing the scheduling overhead in terms of task migrations. …”
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A new modified differential evolution algorithm scheme-based linear frequency modulation radar signal de-noising
Published 2015“…The main intention of this study was to investigate the development of a new optimization technique based on the differential evolution (DE) algorithm, for the purpose of linear frequency modulation radar signal de-noising. …”
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Performance comparison of differential evolution and particle swarm optimization in constrained optimization
Published 2012“…Particle swarm optimization (PSO) and differential evolution (DE) are among the well-known modern optimization algorithms. …”
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Crossover-first differential evolution for improved global optimization in non-uniform search landscapes
Published 2015“…The differential evolution (DE) algorithm is currently one of the most widely used evolutionary-based optimizers for global optimization due to its simplicity, robustness and efficiency. …”
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Reliably optimal PMU placement using disparity evolution-based genetic algorithm
Published 2017“…In this paper, Disparity Evolution-type Genetic Algorithm (DEGA) based on disparity theory of evolution is applied. …”
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Differential evolution optimization algorithm based on generation systems reliability assessment integrated with wind energy
Published 2019“…This stuffy proposed a novel optimization method labeled the "Differential Evolution Optimization Algorithm" (DEOA) to assess the reliability of power generation systems (PGS). …”
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Hybrid algorithm for NARX network parameters' determination using differential evolution and genetic algorithm
Published 2013“…The proposed algorithm involves a two level optimization scheme to search for both optimal network architecture and weights. …”
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Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain
Published 2018“…BSA gave the best overall performance by showing improved solutions and more robust convergence in comparison with various metaheuristics used in this work. Multi-objective optimization problems are also addressed by proposing a modified multi-criterion optimization algorithm based on a Pareto-based Particle Swarm Optimization (PSO) algorithm called Multi-Objective Particle Swarm Optimization (MOPSO). …”
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Hybrid differential evolution-particle swarm optimization algorithm for multi objective urban transit network design problem with homogeneous buses
Published 2019“…This paper proposes a hybrid differential evolution with particle swarm optimization (DE-PSO) algorithm to solve the UTNDP, aiming to simultaneously optimize route configuration and service frequency with specific objectives in minimizing both the passengers’ and operators’ costs. …”
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