首页|New Intelligent Systems Study Findings Recently Were Reported by Researchers at Hunan University (An Improved Fruit Fly Optimization Algorithm With Q-learning f or Solving Distributed Permutation Flow Shop Scheduling Problems)
New Intelligent Systems Study Findings Recently Were Reported by Researchers at Hunan University (An Improved Fruit Fly Optimization Algorithm With Q-learning f or Solving Distributed Permutation Flow Shop Scheduling Problems)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-Investigators publish new report on Machine Learn ing - Intelligent Systems. According to news reporting originating from Hunan, P eople's Republic of China, by NewsRx correspondents, research stated, "The distr ibuted permutation flow shop scheduling problem (DPFSP) is one of the hottest is sues in the context of economic globalization. In this paper, a Q-learning enhan ced fruit fly optimization algorithm (QFOA) is proposed to solve the DPFSP with the goal of minimizing the makespan." Funders for this research include National Natural Science Foundation of China ( NSFC), National Natural Science Foundation of China (NSFC), Natural Science Foun dation of Hunan Province, Young Talent of Lifting Engineering for Science and Te chnology in Hunan Province, Outstanding Youth Project of Education Department of Hunan Province, Key Project of Education Department of Hunan Province of china.
HunanPeople's Republic of ChinaAsiaIntelligent SystemsMachine LearningAlgorithmsHunan University
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