FMS scheduling through artificial neural network

인공 뉴럴 네트워크에 의한 FMS 일정관리

Recently, neural network is recognized as a new approach to solve jobshop scheduling problems in manufacturing system. Scheduling problem is known to be a difficult combinational explosive problem with domain-dependence variations in general. In addition, the needs to achieve a good performance in flexible manufacturing system increase the dimensions of decision complexity. Therefore, mathematical approach to solve realistic problems could be failed to find optimal or optimal-trending. In this paper a technique with neural network for jobs grouping by job-attributes and Gaussian machine network for generating to near-optimal sequence is presented.