Results 11 to 20 of about 51,530 (240)
Journal of Electrical Systems and Information Technology, 2023 Metaheuristic algorithms have become popular in solving engineering optimization problems due to their advantages of simple implementation and the ability to find near-optimal solutions for complex and large-scale problems.
Shamte Kawambwa, Daudi Mnyanghwalo
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Engineering Science and Technology, an International Journal, 2023 Metaheuristic optimization algorithms are global optimization approaches that manage the search process to efficiently explore search spaces associated with different optimization problems. Seahorse optimization (SHO) is a novel swarm-based metaheuristic
Feyza Altunbey Özbay
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A new methodology called dice game optimizer for capacitor placement in distribution systems [PDF]
, 2020 Purpose. Shunt capacitors are installed in power system for compensating reactive power. Therefore, feeder capacity releases, voltage profile improves and power loss reduces.
Al-Haddad, Kamal +5 more
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Firefly Algorithms for Multimodal Optimization [PDF]
, 2009 Nature-inspired algorithms are among the most powerful algorithms for optimization. This paper intends to provide a detailed description of a new Firefly Algorithm (FA) for multimodal optimization applications.
Yang, Xin-She
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PLoS ONE, 2021 Metaheuristic optimization algorithms are one of the most effective methods for solving complex engineering problems. However, the performance of a metaheuristic algorithm is related to its exploration ability and exploitation ability.
Jiahao Fan, Ying Li, Tan Wang
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Sand cat swarm optimization-based feedback controller design for nonlinear systems
Heliyon, 2023 The control of the open loop unstable systems with nonlinear structure is challenging work. In this paper, for the first time, we present a sand cat swarm optimization (SCSO) algorithm-based state feedback controller design for open-loop unstable systems.
Vahid Tavakol Aghaei +3 more
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Firefly Algorithm: Recent Advances and Applications [PDF]
, 2013 Nature-inspired metaheuristic algorithms, especially those based on swarm intelligence, have attracted much attention in the last ten years. Firefly algorithm appeared in about five years ago, its literature has expanded dramatically with diverse ...
He, Xingshi, Yang, Xin-She
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Enhanced Metaheuristic Optimization: Wind-Driven Flower Pollination Algorithm
IEEE Access, 2019 The flower pollination algorithm is a new metaheuristic optimization technique that simulates the pollination behavior of flowers in nature. The global and local search processes of the algorithm are performed by simulating the self-pollination and cross-
Mengyi Lei, Yongquan Zhou, Qifang Luo
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Accelerated Particle Swarm Optimization and Support Vector Machine for Business Optimization and Applications [PDF]
, 2011 Business optimization is becoming increasingly important because all business activities aim to maximize the profit and performance of products and services, under limited resources and appropriate constraints.
A. Chatterjee +23 more
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Online metaheuristic algorithm selection
Expert Systems with Applications, 2022 The performance of optimization algorithms significantly depends on the landscape of the problems. It is known that there is no single algorithm that outperforms others on problems with different fitness landscapes. One of the issues in metaheuristic algorithms is keeping the balance between exploration and exploitation.
Kazem Meidani +2 more
openaire +2 more sources