Zobrazeno 1 - 10
of 29
pro vyhledávání: '"Noor H. Awad"'
Publikováno v:
IJCAI
Modern machine learning algorithms crucially rely on several design decisions to achieve strong performance, making the problem of Hyperparameter Optimization (HPO) more important than ever. Here, we combine the advantages of the popular bandit-based
Publikováno v:
Applied Soft Computing. 76:445-458
Optimal active–reactive power dispatch problems (OARPD) are non-convex and highly nonlinear complex optimization problems. Typically, such problems are expensive in terms of computational time and cost due to the load variations over the scheduling
Publikováno v:
CEC
This paper introduces an enhancement of the recent developed Gaining Sharing Knowledge based algorithm, dubbed as GSK. This algorithm is an excellent example of a contemporary nature-based algorithm which is inspired from the human life behavior of g
Autor:
Marius Lindauer, Gresa Shala, Frank Hutter, Noor H. Awad, André Biedenkapp, Steven Adriaensen
Publikováno v:
Parallel Problem Solving from Nature – PPSN XVI ISBN: 9783030581114
PPSN (1)
PPSN (1)
An algorithm’s parameter setting often affects its ability to solve a given problem, e.g., population-size, mutation-rate or crossover-rate of an evolutionary algorithm. Furthermore, some parameters have to be adjusted dynamically, such as lowering
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0b974a2e3deaba47a4bc6705e342a78f
https://doi.org/10.1007/978-3-030-58112-1_48
https://doi.org/10.1007/978-3-030-58112-1_48
Publikováno v:
Information Sciences. 447:12-35
Over the last few decades, a plethora of improved evolutionary algorithms was developed with exquisite performance on numerical and real-world problems . Among such algorithms, the Cultural Algorithm is a hyper-heuristic evolutionary algorithm, which
Publikováno v:
Swarm and Evolutionary Computation. 39:141-156
Many parameter adaptation methods were proposed for Differential Evolution (DE) algorithm. Although these methods succeed in enhancing the performance of DE when solving a diverse set of optimization problems, locating the optimal solution is still a
Autor:
Ali Shatnawi, Mostafa Z. Ali, Robert G. Reynolds, Ponnuthurai Nagaratnam Suganthan, Noor H. Awad
Publikováno v:
Neurocomputing. 275:155-166
Over the last few decades, many improved Evolutionary Algorithms (EAs) have been proposed to tackle different types of optimization problems. Genetic Algorithm (GA) among other canonical algorithms have not shown consistent performance over a range o
Publikováno v:
Information Sciences. 378:215-241
Many real-world problems can be formulated as optimization problems. Such problems pose a challenge for researchers in the design of efficient algorithms capable of finding the best solution with the least computational cost. In this paper, a new evo
Autor:
Noor H. Awad
Engineers and scientists from all disciplines often have to tackle numerous real- world applications. Developing efficient evolutionary algorithms for this target has attracted many researchers due to the fact that many real-world applications can be
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::200f084dd6c7609bab17b7f0636de37b
https://doi.org/10.32657/10220/48011
https://doi.org/10.32657/10220/48011
Publikováno v:
Information Sciences. 372:470-491
The aim of hybridization in the context of evolutionary computation is to combine appropriate operators from different evolutionary computation paradigms to form a single technique that enjoys a statistically superior performance over a wide range of