自动化学报2008，Vol.34Issue(6)：697-701,5.
基于耦合瞬态混沌神经网络的同等并行机调度
A Coupled Transiently Chaotic Neural Network Approach for Identical Parallel Machine Scheduling
摘要
Abstract
Scheduling jobs on identical machines is a situation frequently encountered in various manufacturing systems. In this paper, a new coupled transiently chaotic neural network (CTCNN) is put forward to solve identical parallel machine scheduling. A mixed integer programming model of this problem is transformed into a CTCNN computation architecture by introducing a permutation matrix expression. A new computational energy function is proposed to express the objective besides all the constraints. In particular, the tradeoff problem existing among the penalty terms in the energy function is overcome by using time-varying penalty parameters. Finally, results tested on 3 different scale problems with 100 random initial conditions show that the network converges and can solve these problems in the reasonable time.关键词
Scheduling, identical parallel machines/coupled transiently chaotic neural network/time-varying penalty coefficientsKey words
Scheduling, identical parallel machines/coupled transiently chaotic neural network/time-varying penalty coefficients分类
信息技术与安全科学引用本文复制引用
于艾清,顾幸生..基于耦合瞬态混沌神经网络的同等并行机调度[J].自动化学报,2008,34(6):697-701,5.基金项目
Supported by National Natural Science Foundation of China (60674075,60774078) （60674075,60774078）
