دانلود مقاله انگلیسی رایگان:یک شبکه اشاره گر مبتنی بر الگوریتم یادگیری عمیق برای مسئله برنامه نویسی درجه دوم باینری نامحدود - 2020
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  • A pointer network based deep learning algorithm for unconstrained binary quadratic programming problem A pointer network based deep learning algorithm for unconstrained binary quadratic programming problem
    A pointer network based deep learning algorithm for unconstrained binary quadratic programming problem

    سال انتشار:

    2020


    عنوان انگلیسی مقاله:

    A pointer network based deep learning algorithm for unconstrained binary quadratic programming problem


    ترجمه فارسی عنوان مقاله:

    یک شبکه اشاره گر مبتنی بر الگوریتم یادگیری عمیق برای مسئله برنامه نویسی درجه دوم باینری نامحدود


    منبع:

    Sciencedirect - Elsevier - Neurocomputing, 390 (2020) 1-11. doi:10.1016/j.neucom.2019.06.111


    نویسنده:

    Shenshen Gu ∗, Tao Hao , Hanmei Yao


    چکیده انگلیسی:

    Combinatorial optimization problems have been widely used in various fields. And many types of com- binatorial optimization problems can be generalized into the model of unconstrained binary quadratic programming (UBQP). Therefore, designing an effective and efficient algorithm for UBQP problems will also contribute to solving other combinatorial optimization problems. Pointer network is an end-to-end sequential decision structure and combines with deep learning technology. With the utilization of the structural characteristics of combinatorial optimization problems and the ability to extract the rule be- hind the data by deep learning, pointer network has been successfully applied to solve several classical combinatorial optimization problems. In this paper, a pointer network based algorithm is designed to solve UBQP problems. The network model is trained by supervised learning (SL) and deep reinforcement learning (DRL) respectively. Trained pointer network models are evaluated by self-generated benchmark dataset and ORLIB dataset respectively. Experimental results show that pointer network model trained by SL has strong learning ability to specific distributed dataset. Pointer network model trained by DRL can learn more general distribution data characteristics. In other words, it can quickly solve problems with great generalization ability. As a result, the framework proposed in this paper for UBQP has great potential to solve large scale combinatorial optimization problems.
    Keywords: UBQP | Pointer network | Supervised learning | Deep reinforcement learning


    سطح: متوسط
    تعداد صفحات فایل pdf انگلیسی: 11
    حجم فایل: 610 کیلوبایت

    قیمت: رایگان


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