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361
Multi-Objective Task Allocation Via Multi-Agent Coalition Formation
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doctoralThesis -
362
An Uncertainty Based Genetic Algorithm Approach for Project Resource Scheduling
Published 2016“…The results showed the proposed methodology outperformed existing algorithms in optimizing project durations and resources allocation. …”
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363
Incremental & classical genetic algorithm. (c2001)
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masterThesis -
364
A new multimodulus blind equalization algorithm
Published 2004“…The phase-recovery and intersymbol interference optimization properties, exhibited by the proposed algorithm, are also discussed.…”
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365
A simulated annealing algorithm for unit commitment
Published 1998“…This paper presents a simulated annealing algorithm (SAA) to solve the unit commitment problem (UCP). …”
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366
A SIMULATED ANNEALING ALGORITHM FOR THE CLUSTERING PROBLEM
Published 2020“…In this paper we discuss the solution of the clustering problem usually solved by the K-means algorithm. The problem is known to have local minimum solutions which are usually what the K-means algorithm obtains. …”
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367
Adaptive bias simulated evolution algorithm for placement
Published 2001“…Simulated Evolution (SE) is a general meta-heuristic for combinatorial optimization problems. A new solution is evolved from current solution by relocating some of the solution elements. …”
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368
A New Parallel Genetic Algorithm Model
Published 2020“…This paper presents an implementation of three Genetic Algorithm models for solving a reliability optimization problem for a redundancy system with several failure modes, a modification on a parallel a genetic algorithm model and a new parallel genetic algorithm model. …”
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369
Artificial neural network algorithms. (c1999)
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masterThesis -
370
A Literature Review on System Dynamics Modeling for Sustainable Management of Water Supply and Demand
Published 2023“…The models included agent-based modeling (ABM), Bayesian networking (BN), analytical hierarchy approach (AHP), and simulation optimization multi-objective optimization (MOO). The solution approaches included the genetic algorithm (GA), particle swarm optimization (PSO), and the non-dominated sorting genetic algorithm (NSGA-II). …”
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371
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372
Multilayer Reversible Data Hiding Based on the Difference Expansion Method Using Multilevel Thresholding of Host Images Based on the Slime Mould Algorithm
Published 2022“…The slime mould algorithm (SMA) gives good results in finding the best solutions to optimization problems. …”
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373
Bridge Structural Health Monitoring Using Mobile Sensor Networks
Published 2022Get full text
doctoralThesis -
374
Software defect prediction. (c2019)
Published 2019“…One that focuses on predicting defect in software modules using a hybrid heuristic - a combination of Particle Swarm Optimization (PSO) and Genetic Algorithms (GA). We compare our approach to 9 well known machine learning techniques and results show the advantages of our model over the other techniques. …”
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masterThesis -
375
Multiobjective Evolutionary Algorithms for Electric Power Dispatch Problem
Published 2006“…The potential and effectiveness of the newly developed Pareto-based multiobjective evolutionary algorithms (MOEA) for solving a real-world power system multiobjective nonlinear optimization problem are comprehensively discussed and evaluated in this paper. …”
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376
Multiobjective evolutionary algorithms for electric power dispatch problem
Published 2006“…The potential and effectiveness of the newly developed Pareto-based multiobjective evolutionary algorithms (MOEA) for solving a real-world power system multiobjective nonlinear optimization problem are comprehensively discussed and evaluated in this paper. …”
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377
Control of nonlinear dynamical systems using genetic algorithms
Published 1997“…This paper introduces a new method for the control of nonlinear systems using genetic algorithms. The proposed method formulates the nonlinear controller design as an optimization problem and genetic algorithms are used in the optimization process. …”
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378
Capturing outline of fonts using genetic algorithm and splines
Published 2001“…We present a method to convert the original problem into a discrete combinatorial optimization problem and solve it by a genetic algorithm. …”
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379
Inferential sensing techniques in industrial applications
Published 0007“…System delays are obtained by approximating the model by a linear model. Genetic algorithm, which is a heuristic optimization technique, is used to ¯nd the system delays of the linear model, which are used in dynamical neural network model. …”
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masterThesis -
380
Computational Experience On Four Algorithms For The Hard Clustering Problem
Published 2020“…Several algorithms have been developed to solve this problem which include the k-means algorithm, the simulated annealing algorithm, the tabu search algorithm, and the genetic algorithm. …”
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