基于标量化方法的一类双层双目标规划问题的人工神经网络。
The Artificial Neural Networks Based on Scalarization Method for a Class of Bilevel Biobjective Programming Problem.
机构信息
School of Information and Mathematics, Yangtze University, Jingzhou 434023, China.
School of Management, Huaibei Normal University, Huaibei 235000, China.
出版信息
Comput Intell Neurosci. 2017;2017:1853131. doi: 10.1155/2017/1853131. Epub 2017 Sep 14.
A two-stage artificial neural network (ANN) based on scalarization method is proposed for bilevel biobjective programming problem (BLBOP). The induced set of the BLBOP is firstly expressed as the set of minimal solutions of a biobjective optimization problem by using scalar approach, and then the whole efficient set of the BLBOP is derived by the proposed two-stage ANN for exploring the induced set. In order to illustrate the proposed method, seven numerical examples are tested and compared with results in the classical literature. Finally, a practical problem is solved by the proposed algorithm.
提出了一种基于标量化方法的双层双目标规划问题（BLBOP）的两阶段人工神经网络（ANN）。通过标量化方法，将 BLBOP 的诱导集表示为双目标优化问题的最小解集，然后通过提出的两阶段 ANN 导出 BLBOP 的整个有效集，以探索诱导集。为了说明所提出的方法，测试了七个数值实例，并与经典文献中的结果进行了比较。最后，通过所提出的算法解决了一个实际问题。
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