Bilevel optimization based on foraging by different ant species for real-time transportation planning

IF 2.3 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Evolutionary Intelligence Pub Date : 2023-11-29 DOI:10.1007/s12065-023-00890-8

S. S. Vinod chandra, R. Saritha

引用次数: 0

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基于不同蚂蚁种类觅食的双层优化，用于实时交通规划

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Evolutionary Intelligence COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-

CiteScore

6.80

自引率

0.00%

发文量

108

期刊介绍： This Journal provides an international forum for the timely publication and dissemination of foundational and applied research in the domain of Evolutionary Intelligence. The spectrum of emerging fields in contemporary artificial intelligence, including Big Data, Deep Learning, Computational Neuroscience bridged with evolutionary computing and other population-based search methods constitute the flag of Evolutionary Intelligence Journal.Topics of interest for Evolutionary Intelligence refer to different aspects of evolutionary models of computation empowered with intelligence-based approaches, including but not limited to architectures, model optimization and tuning, machine learning algorithms, life inspired adaptive algorithms, swarm-oriented strategies, high performance computing, massive data processing, with applications to domains like computer vision, image processing, simulation, robotics, computational finance, media, internet of things, medicine, bioinformatics, smart cities, and similar. Surveys outlining the state of art in specific subfields and applications are welcome.