Simulated evolution for timing and low power VLSI standard cell placement by Sait, Sadiq M.

“…For this hard multiobjective combinatorial optimization problem, no known exact and efficient algorithms exist that guarantee finding a solution of specific or desirable quality. …”
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Data Generation for Path Testing by Mansour, Nashat

“…The two algorithms are: a simulated annealing algorithm (SA), and a genetic algorithm (GA). …”
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Final exams scheduling for univeristies. (c2001) by Timany, Mazen Nuhad

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Joint Planning of Smart EV Charging Stations and DGs in Eco-Friendly Remote Hybrid Microgrids by Shaaban, Mostafa

“…The planning problem jointly allocates and sizes a set of distributed generators (DGs) along with the EV charging stations to balance the supply with the total demand of regular loads and EV charging. The planning algorithm specifies optimal locations and sizes of the EV charging stations and DG units that minimize two conflicting objectives: (a) deployment and operation costs and (b) associated green house gas emissions, while satisfying the microgrid technical constraints. …”
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Impacts of On-Grid Solar PV on Distribution Networks and Potential Solutions: A Case Study in the Region of Zahle by Korkmaz, Jessica

“…The siting and sizing methodology is conducted by considering five different optimization algorithms, namely the single-objective genetic algorithm (SOGA), the combined SOGA and loss sensitivity factor algorithm (SOGA-LSF), the multi-objective genetic algorithm (MOGA), the combined MOGA-LSF and the CAPADD algorithm of OpenDSS. …”
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Tuning of AGC of interconnected reheat thermal systems with geneticalgorithms by Abdel-Magid, Y.L.

“…This paper deals with the application of genetic algorithms for optimizing the automatic generation control (AGC) systems. …”
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Graph Contraction for Mapping Data on Parallel Computers by Mansour, N.

“…We then present experimental results on using contracted graphs as inputs to two physical optimization methods; namely, genetic algorithm and simulated annealing. …”
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A novel network-based SIS framework for improved GA performance by Tohme, Rawane

“…Genetic algorithms have long been used to solve complex optimization problems by mimicking natural selection processes. …”
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Nested ensemble selection: An effective hybrid feature selection method by Kamalov, Firuz

“…Numerical experiments on synthetic and real-life data demonstrate the effectiveness of the proposed method. The NES algorithm achieves perfect precision on the synthetic data and near optimal accuracy on the real-life data. …”
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Localization of Damages in Plain And Riveted Aluminium Specimens using Lamb Waves by S. Andhale, Yogesh

“…The genetic optimization (GO) method is used to further refine the location of damage within the enclosed area obtained using astroid algorithm. …”
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Enhancement of Frequency Control for Stand-Alone Multi-Microgrids by Kavita Singh (182141)

“…For getting superior outcomes and enhanced steadiness of the microgrid, the controller gains are streamlined utilizing an imperialist competitive algorithm (ICA). To demonstrate the efficiency of ICA, The obtained results are compared with the genetic algorithm and particle swarm optimization algorithm. …”

Cost-Benefit Analysis of Genotype-Guided Interruption Days in Warfarin Pre-Procedural Management by Islam Eljilany (14151588)

“…As per 10.3% prevalence of genetic variants, 82% bridging, and a calculated 20% optimization in the preparative period of warfarin management, the benefit to cost ratio was 4.0 in favor genotype-guided approach. …”

Parallel processing by Mansour, Nashat

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Finite state machine state assignment for area and power minimization by El-Maleh, A.

“…A fuzzy-based aggregation function is employed to combine the two objectives. The work employs genetic algorithm for search space exploration. Experimental results demonstrate the effectiveness of the proposed measures.…”
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Scheduling and allocation in high-level synthesis using stochastic techniques by Sait, Sadiq M.

“…Scheduling and allocation can be formulated as an optimization problem. In this work, a unique approach to scheduling and allocation problem using the genetic algorithm (GA) is described. …”
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A new variable structure DC motor controller using geneticalgorithms by Al-Hamouz, Z.M.

“…This paper presents a new application of the genetic algorithm for the selection of the variable structure controller (VSC) feedback gains and switching vector for a separately excited DC motor. …”
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A simulated evolution approach to task-matching and scheduling in heterogeneous computing environments by Barada, Hassan

“…The performance of SE is compared with a genetic algorithm approach for the same problem with respect to the quality of solutions generated, and timing requirements of the algorithms. r 2003 Elsevier Science Ltd. …”
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A new bi-objective model of the urban public transportation hub network design under uncertainty by Firoozeh Kaveh (14150877)

“…Since exact values of some parameters are not known in advance, a fuzzy multi-objective programming based approach is proposed to optimally solve small-sized problems. For medium and large-sized problems, a meta-heuristic algorithm, namely multi-objective particle swarm optimization is applied and its performance is compared with results from the non-dominated sorting genetic algorithm. …”

Test bus assignment, sizing, and partitioning for system-on-chip by Harmanani, Haidar M.

“…In this paper, an efficient genetic algorithm for designing test access architectures while investigating test bus sizing and concurrently assigning cores to test buses is proposed. …”
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DSCE: Comparative Analysis of Heuristic Computational Techniques by Bany Muhammad, Nooh

“…Various HCTs are also compared, including genetic algorithms (GAs), particle swarm optimization (PSO), differential evolution (DE), cat swarm optimization (CSO), bee colony optimization (BCO), hybrid GA-PSO (HGP), and the cuckoo search algorithm (CSA). …”
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