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Titlebook: Applied Multi-objective Optimization; Nilanjan Dey Book 2024 The Editor(s) (if applicable) and The Author(s), under exclusive license to S

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發(fā)表于 2025-3-21 18:11:10 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱Applied Multi-objective Optimization
影響因子2023Nilanjan Dey
視頻videohttp://file.papertrans.cn/160/159969/159969.mp4
發(fā)行地址Explains basic ideas behind several kinds of applied multi-objective optimization.How meta-heuristic algorithms are successful in resolving challenging, multi-objective optimization issues.Serves as a
學(xué)科分類Springer Tracts in Nature-Inspired Computing
圖書封面Titlebook: Applied Multi-objective Optimization;  Nilanjan Dey Book 2024 The Editor(s) (if applicable) and The Author(s), under exclusive license to S
影響因子.The book explains basic ideas behind several kinds of applied multi-objective optimization and shows how it will be applied in practical contexts in the domain of healthcare, engineering design, and manufacturing. The book discusses how meta-heuristic algorithms are successful in resolving challenging, multi-objective optimization issues in various disciplines, including engineering, economics, medical and environmental management. The topic is useful for graduates, researchers and lecturers in optimization, engineering, management science and computer science.?.
Pindex Book 2024
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Multi-objective Adaptive Guided Differential Evolution for Passively Controlled Structures Equippeded Differential Evolution (MOAGDE). The TMD system is widely employed to mitigate structural vibrations and enhance the dynamic behavior of structures. However, the optimization of TMD-based systems often involves conflicting objectives, such as various seismic responses. To address this challenge,
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Multi-objective Lichtenberg Algorithm for the Optimum Design of Truss Structures,eously optimize two conflicting objectives: the truss weight and nodal displacement. The Lichtenberg algorithm (LA) draws inspiration from the natural occurrence of radial intracloud lightning and the formation of Lichtenberg figures. It effectively harnesses the fractal nature of these phenomena to
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Multi-modal Routing in Urban Transportation Network Using Multi-objective Quantum Particle Swarm Opon (MOQPSO) approach. The transportation network under consideration encompasses subways, buses, taxis, and walking routes. The objective is to minimize the overall route length while ensuring efficiency through the incorporation of five specific changes along the route. The routing problem inherent
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Applied Multi-objective Optimization978-981-97-0353-1Series ISSN 2524-552X Series E-ISSN 2524-5538
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