ProceedingsIEEE, 1997 - Artificial intelligence |
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Page 224
... represents the long term cost of being in configuration ceC for se S. Similarly , F ( s , c ) represents the single stage cost of being in configuration ce C for se S. Initially the costs in each state are estimated as the single stage ...
... represents the long term cost of being in configuration ceC for se S. Similarly , F ( s , c ) represents the single stage cost of being in configuration ce C for se S. Initially the costs in each state are estimated as the single stage ...
Page 313
... represented by genetic algorithm [ 7 ] , artificial neural network [ 8 ] and ant algorithm [ 15 ] scheduling approaches ( SAs ) . Finally , the Scheduling Method class represents application - specific SMs , which apply algorithms based ...
... represented by genetic algorithm [ 7 ] , artificial neural network [ 8 ] and ant algorithm [ 15 ] scheduling approaches ( SAs ) . Finally , the Scheduling Method class represents application - specific SMs , which apply algorithms based ...
Page 474
... represent ' AND ' and ' OR ' respectively , and I represents the negation of I5 . The Enable Signals signals which change the step to activity on the input condition ( I3,14 ) The Disable Signal signals which change the step to ...
... represent ' AND ' and ' OR ' respectively , and I represents the negation of I5 . The Enable Signals signals which change the step to activity on the input condition ( I3,14 ) The Disable Signal signals which change the step to ...
Contents
Innovations in Design and Integrated | 1 |
Creative and Innovative Manufacturing | 4 |
Y Fan and C Wu Tsinghua Univ | 7 |
Copyright | |
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according activities algorithm allows analysis application approach architecture assembly ATRT Automation called communication complete components considered constraints control system cost customers decision defined described determined dispatching distributed dynamic effective Engineering enterprise environment error estimated example exists Figure fixture flexible flow function given implementation important improvement industrial input integration interaction interface INTRODUCTION knowledge lead learning load locating machine manuals manufacturing means measurements method nets object obtained operation optimal output parameters performance Petri planning plant position possible presented problem proposed prototype real-time reference represents requirements robot rules scheduling selected sequence server shown shows simulation solution specific standard station structure task token tool transition unit University virtual