Applied (Meta)-Heuristic in Intelligent Systems
Engineering and business problems are becoming increasingly difficult to solve due to the new economics triggered by big data, artificial intelligence, and the internet of things. Exact algorithms and heuristics are insufficient for solving such large and unstructured problems; instead, metaheuristi...
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Format: | Electronic Book Chapter |
Language: | English |
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Basel
MDPI - Multidisciplinary Digital Publishing Institute
2022
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Online Access: | DOAB: download the publication DOAB: description of the publication |
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520 | |a Engineering and business problems are becoming increasingly difficult to solve due to the new economics triggered by big data, artificial intelligence, and the internet of things. Exact algorithms and heuristics are insufficient for solving such large and unstructured problems; instead, metaheuristic algorithms have emerged as the prevailing methods. A generic metaheuristic framework guides the course of search trajectories beyond local optimality, thus overcoming the limitations of traditional computation methods. The application of modern metaheuristics ranges from unmanned aerial and ground surface vehicles, unmanned factories, resource-constrained production, and humanoids to green logistics, renewable energy, circular economy, agricultural technology, environmental protection, finance technology, and the entertainment industry. This Special Issue presents high-quality papers proposing modern metaheuristics in intelligent systems. | ||
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650 | 7 | |a Technology: general issues |2 bicssc | |
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653 | |a matheuristics | ||
653 | |a hyperheuristics | ||
653 | |a vehicle routing | ||
653 | |a wireless networking | ||
653 | |a green energy | ||
653 | |a low carbons  | ||
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856 | 4 | 0 | |a www.oapen.org |u https://directory.doabooks.org/handle/20.500.12854/94566 |7 0 |z DOAB: description of the publication |