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  1. 101

    Multiobjective Evolutionary Algorithms for Electric Power Dispatch Problem by Abido, M. A.

    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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  2. 102

    Multiobjective evolutionary algorithms for electric power dispatch problem by Abido, M.A.

    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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  3. 103

    Computational Experience On Four Algorithms For The Hard Clustering Problem by AlSultan, K.S.

    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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  4. 104

    Evolutionary algorithms for VLSI multi-objective netlist partitioning by Sait, Sadiq M.

    Published 2006
    “…In this paper, we engineer three iterative heuristics for the optimization of VLSI netlist bi-partitioning. These heuristics are based on Genetic Algorithms (GAs), Tabu Search (TS) and Simulated Evolution (SimE). …”
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  5. 105
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    An evolutionary algorithm for solving the geometrically constrained site layout problem by Zouein, P.

    Published 2017
    “…The proposed algorithm is two-phases: an initialization phase that generates an initial population of layouts through a sequence of mutation operations, and a reproduction phase that evolve the layouts generated in phase one through a sequence of genetic operations aiming at finding an optimal layout. …”
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    Evolutionary algorithms, simulated annealing and tabu search: a comparative study by Youssef, H.

    Published 2020
    “…All rights reserved. Keywords: Genetic algorithms; Simulated annealing; Tabu search; Fuzzy logic; Floorplanning; Combinatorial optimization; VLSI…”
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  10. 110

    On-site workshop investment problem: A novel mathematical approach and solution procedure by Nima Moradi (19418821)

    Published 2023
    “…Next, due to the NP-hardness of the problem, an enhanced Genetic Algorithm (GA)-based metaheuristic with efficient problem-specific improvement rules as local search and effective crossover and mutation operators is proposed. …”
  11. 111

    A new multiobjective evolutionary algorithm forenvironmental/economic power dispatch by Abido, A.A.

    Published 2001
    “…A new nondominated sorting genetic algorithm (NSGA) based approach is proposed to handle the problem as a true multiobjective optimization problem with competing and noncommensurable objectives. …”
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  12. 112

    Optimizing overheating, lighting, and heating energy performances in Canadian school for climate change adaptation: Sensitivity analysis and multi-objective optimization methodolog... by Mutasim Baba, Fuad

    Published 2023
    “…This paper aims to develop long-term adaptation strategies for the existing Canadian school buildings under extreme current and future climates using a developed methodology based on global and local sensitivity analysis and Multi-Objective Optimization Genetic Algorithm. The calibrated simulation model based on indoor and outdoor measured temperature for a school of interest is used to evaluate the optimization strategies. …”
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  13. 113

    Gene Selection for Microarray Data Classification based on Grey Wolf Optimizer Enhanced with TRIZ-inspired Operators by Abou Doush, Iyad

    Published 2021
    “…Pattern recognition algorithms are widely applied to gene expression data to differentiate between health and cancerous patient samples. …”
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  14. 114
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    Parametric Design Optimization in Sustainable Urban Design: In Hot Climate by Musleh, Mousa A. M.

    Published 2012
    “…This research employs Genetic algorithms as the computational design methodology to achieve parametric design optimization to design for a more sustainable cities and urban. …”
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  16. 116

    Environmental/economic power dispatch using multiobjective evolutionary algorithms: a comparative study by Abido, M.A.

    Published 2003
    “…A comparative study of newly developed Pareto-based multiobjective evolutionary algorithms (MOEA) applied to a nonlinear power system multiobjective optimization problem is presented in this paper. …”
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    Fuzzy simulated evolution for power and performance optimization ofVLSI placement by Sait, Sadiq M.

    Published 2001
    “…This is a hard multiobjective combinatorial optimization problem with no known exact and efficient algorithm that can guarantee finding a solution of specific or desirable quality. …”
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