Showing 1 - 20 results of 533 for search 'multi-objective (whale OR (whole OR while)) optimization algorithm', query time: 0.25s Refine Results
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    Integration of electric vehicle charging stations with distributed generation using multi-objective metaheuristic optimization by Aya Desoky Gaber, E.M. Abdallah, M.I. Elsayed, Ahmed Abdelbaset

    Published 2025-09-01
    “…This paper uses a multi-objective optimization approach metaheuristic algorithm, specifically the Whale Optimization Algorithm (WOA), Zebra Optimization Algorithm (ZOA), and Puma Optimization Algorithm (POA), to determine the optimal size and placement of DG units in the presence of EVCS. …”
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    Comparative Review of Multi-Objective Optimization Algorithms for Design and Safety Optimization in Electric Vehicles by I Gede S. S. Dharma, Rachman Setiawan

    Published 2024-01-01
    “…Despite the widespread use of established optimization algorithms like Non-Dominated Sorting Genetic Algorithm-II (NSGA-II), Non-Dominated Sorting Genetic Algorithm-III (NSGA-III), and Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D) in real-world engineering optimization problems, newer algorithms such as Two-Stage NSGA-II (TS-NSGA-II), Dynamic Constrained NSGA-III (DCNSGA-III), MOEA/D with Virtual Objective Vectors (MOEA/D-VOV), Large-Scale Evolutionary Multi-Objective Optimization Assisted by Directed Sampling (LMOEA-DS), and Super-Large-Scale Multi-Objective Evolutionary Algorithm (SLMEA) remain underexplored in the context of Battery Electric Vehicle (BEV) safety, particularly in optimizing complex, non-linear, and constrained multi-objective problems like crashworthiness and thermal management. …”
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    Exploring Evolutionary Algorithms for Multi-Objective Optimization in Seismic Structural Design by Seda Göktepe Körpeoğlu, Süleyman Mesut Yılmaz

    Published 2024-10-01
    “…While genetic algorithms are used to improve both the cost and seismic performance of the structure, particle swarm optimization is used to optimize the vibration and displacement performance of structures. …”
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    Multi-Objective Robust Optimization Reconstruction Algorithm for Electrical Capacitance Tomography by Xuejie Yang, Jing Lei, Qibin Liu

    Published 2025-04-01
    “…An innovative nested algorithm that mitigates computational difficulties arising from the interactions between the upper- and lower-level optimization problems is proposed to solve the proposed multi-objective robust optimization model. …”
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    Comparison of algorithms for multi-objective optimization of radio technical device characteristics by A. V. Smirnov

    Published 2022-12-01
    “…One of the compared algorithms comprises the Third Evolution Step of Generalized Differential Evolution (GDE3) population-based algorithm for searching the full approximation of the Pareto set simultaneously, while the other three algorithms minimize the scalar objective function to find only one element of the Pareto set in a single search cycle: these comprise Multistart Pattern Search (MSPS), Multistart Sequential Quadratic Programming (MSSQP) method and Particle Swarm Optimization (PSO) algorithms.Results. …”
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    A novel robust multi-objective evolutionary optimization algorithm based on surviving rate by Wenxiang Jiang, Kai Gao, Shuwei Zhu, Lihong Xu

    Published 2025-02-01
    “…Despite the success of multi-objective evolutionary optimization algorithms in addressing complex optimization problems, research focusing on input disturbances remains limited. …”
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    Network reconfiguration and optimal distributed generations allocation with whale optimizer algorithm by Ahmadreza Abdollahi Chirani

    Published 2025-03-01
    “…The multi-objective and multi-constrained feature of the Whale Optimization Algorithm (WOA) makes it a useful optimization technique for network reconfiguration. …”
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    Dual-Population Cooperative Correlation Evolutionary Algorithm for Constrained Multi-Objective Optimization by Junming Chen, Yanxiu Wang, Zichun Shao, Hui Zeng, Siyuan Zhao

    Published 2025-04-01
    “…When addressing constrained multi-objective optimization problems (CMOPs), the key challenge lies in achieving a balance between the objective functions and the constraint conditions. …”
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