Natural optimization algorithms for optimal regression testing by Mansour, Nashat

“…The present two natural optimization algorithms, namely simulated annealing and genetic algorithms, for solving this problem. …”
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Gradient-Based Optimizer (GBO): A Review, Theory, Variants, and Applications by Daoud, Mohammad Sh.

Subjects: “…Gradient-Based Optimizer…”
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An evolutionary algorithm for network topology design by Youssef, H.

“…The topology design of campus networks is a hard constrained combinatorial optimization problem, dictated by physical and technological constraints and must optimize several objectives. …”
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Optimizing transparent photovoltaic integration with battery energy storage systems in greenhouse: a daily light integral-constrained economic analysis considering BESS degradation by Mohammadreza Gholami (17032317)

The Hybrid Framework for Multi-objective Evolutionary Optimization Based On Harmony Search Algorithm by Abu Doush, Iyad

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The Hybrid Framework for Multi-objective Evolutionary Optimization Based On Harmony Search Algorithm by Abou Doush, Iyad

“…In evolutionary multi-objective optimization, an evolutionary algorithm is invoked to solve an optimization problem involving concurrent optimization of multiple objective functions. …”
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Archive-based coronavirus herd immunity algorithm for optimizing weights in neural networks by Abasi, Ammar

“…Coronavirus herd immunity optimizer (CHIO) is a recent metaheuristic human-based algorithm stemmed from the herd immunity mechanism as a way to treat the spread of the coronavirus pandemic. …”
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A multi-objective planning approach for optimal DG allocation for droop based microgrids by Shaaban, Mostafa

“…This paper proposes a multi-objective planning approach to determine the optimal DG locations for droop-based microgrids. A secondary control operating region is mathematically formulated and incor-porated in the multi-objective optimization problem to constrain the optimal droop characteristic within the acceptable frequency and voltage thresholds. …”
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Brain Storm Optimization Algorithm by El-Abd, Mohammed

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Whale optimization algorithm: analysis and full survey by Abualigah, Laith

“…Various adaptations and hybridizations of the WOA are reviewed, including adaptive strategies, constrained and multiobjective optimization extensions, and combinations with other algorithms. …”
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A hybrid heuristic approach to optimize rule based software quality estimation models. (c2008) by Korkmaz, Rita

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Artificial neural network algorithms. (c1999) by Ramadan, Samer N.

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Squirrel Search Algorithm for Portfolio Optimization by Dhaini, Mahdi

“…In this paper, we design and adapt a Squirrel Search Algorithm (SSA) for the unconstrained and constrained portfolio optimization problems. …”
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Animal migration optimization algorithm: novel optimizer, analysis, and applications by Abualigah, Laith

“…A new heuristic optimization algorithm was proposed in 2013 called the animal migration optimization (AMO) algorithm. …”
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Particle swarm optimization based algorithm for protein structure prediction in the 3D HP model. (c2008) by Kanj, Fatima Hassan

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Particle swarm optimization algorithm: review and applications by Abualigah, Laith

“…Particle swarm optimization (PSO) is a heuristic global optimization technique and an optimization algorithm that is swarm intelligence-based. …”
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Automatic Modulation Recognition Based on the Optimized Linear Combination of Higher-Order Cumulants by Asad Hussain (10135049)

Fuzzy simulated evolution algorithm for topology design of campusnetworks by Youssef, H.

“…The topology design of campus networks is a hard constrained combinatorial optimization problem. It consists of deciding the number, type, and location of the active network elements (nodes) and links. …”
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Global-best Brain Storm Optimization Algorithm by El-Abd, Mohammed

“…Brain storm optimization (BSO) is a population-based metaheuristic algorithm that was recently developed to mimic the brainstorming process in humans. …”
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Island flower pollination algorithm for global optimization by Al-Betar, Mohammed Azmi

“…Comparing the results of IsFPA with those of state-of-the-art methods which are FPA, genetic algorithm (GA), particle swarm optimization (PSO), gravitational search algorithm (GSA), multi-verse optimizer (MVO), island bat algorithm (iBA), and island harmony search (iHS), the comparison results show that the IsFPA is able to control the diversity and improves the outcomes where IsFPA is ranked first followed by FPA, iBA, iHS, GSA, MVO, GA, PSO, respectively, based on the Friedman test with Holm and Hochberg as post hoc statistical test.…”
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