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Meeting Agenda 05-21-14. Overview ( 概观 ) Weighted Neural Network Training ( 平方差比重定制 ) Optimization algorithm update ( 优化算法更新 ). (1) Overview ( 概观 ). Previous Week and Current Week: Weight trained for neural network (60 40 split) ( 平方差比重定制 )
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Meeting Agenda 05-21-14 • Overview (概观) • Weighted Neural Network Training (平方差比重定制) • Optimization algorithm update (优化算法更新)
(1) Overview (概观) • Previous Week and Current Week: • Weight trained for neural network (60 40 split) (平方差比重定制) • Modified the GA so that it requires no starting point (60%的工时达成率,40%成套率) • Next Week: • Optimization algorithm update. (优化算法更新)
(2) Weighted Neural Network training • The neural network can be adjusted so that the Completion percentage has a higher weight value than Assembly readiness (60% for completion % and 40% for Assembly readiness). (已调整神经网络比重: 60%的工时达成率,40%成套率) • The weights can also be adjusted so that a higher significance is placed on completion % during the initial months and assembly readiness during the later months. (比重可由使用者自行指定)
(3) Optimization algorithm update • The optimization algorithm has been updated so that it requires no initial starting point. (优化算法已更新, 无需初始点) • During the simulation a 20 minute limit was placed on the run time for the algorithm in order to simulate real life situation. (优化执行20分钟,大约5-10代) • Please see Excel for results
(3) Optimization algorithm update • Conclusion • The optimization algorithm is able to find a feasible starting point and optimize it within the given time. (优化算法能够找优化算法能够在时间内找到可行的初始点进行优化) • The optimization algorithm is slightly unstable at this point. This happens because the delays are being optimized it tries to move incrementally (10.9 – 10.8 – 10.4). (优化算法有时候不稳定,延迟增量剧增剧减) • If the algorithm is unable to find a set of feasible starting points it stops the execution and gives an infeasible output. (如果优化算法无法找到一组可行的起始点,将停止执行)
(3) Optimization algorithm update • Future steps. • Instead of optimizing the delays the algorithm is being modified so that it follows some physical rules. (给予优化算法规则) • The algorithm will first place the steps one after another and then try and find the sequence of steps that will maximize the KPI. (規則一:嘗試找出最優化的零件,批次順序) • By doing this, only the sequence is being optimized rather than delays which moves incrementally. (先優化零件,批次順序, 依序优化延迟)