部分可观标签时间Petri网的最小代价变迁序列估计OA北大核心CSTPCD

Aiming at the problem of planning sequences in automated manufacturing systems,this study proposes an approach to solve the least-cost transition sequence estimation problem in a partially observable labeled time Petri net(LTPN).In particular,the considered LTPN is bounded,where each transition has a nonnegative cost.Based on time-label sequences(TLS),we first introduce a graph called observed-modified state class graph(OSCG)that represents the partial state space of an LTPN system.Then,all transition sequences logically consistent with the observed TLS can be found in the OSCG.By exploiting the transition-related timing constraints in an OSCG,we propose a procedure for determining which logic-consistent transition sequences are timing consistent with the observed TLS.Then,we develop an algorithm for estimating the least-cost transition sequences.Finally,the effectiveness of the proposed method is verified using an experimental example.