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學(xué)術(shù)動(dòng)態(tài)

學(xué)術(shù)動(dòng)態(tài)

學(xué)術(shù)活動(dòng)

講座題目:On the construction of optimal policies for the RCPSP with stochastic activity durations

作者: 編輯: 發(fā)布時(shí)間:2019-07-15

時(shí)    間:7月17日(周三)上午10:00-11:30

地    點(diǎn):bwin必贏唯一官網(wǎng)313會(huì)議室

主講人:Erik Demeulemeester教授

 

主講人簡(jiǎn)介:

Erik Demeulemeester,比利時(shí)荷語(yǔ)魯汶大學(xué)經(jīng)濟(jì)與商學(xué)院教授,運(yùn)營(yíng)管理研究中心主任,主要研究領(lǐng)域?yàn)轫?xiàng)目調(diào)度、醫(yī)療調(diào)度等,主要講授項(xiàng)目與生產(chǎn)調(diào)度、組合優(yōu)化與局部?jī)?yōu)化算法、生產(chǎn)與物流等課程?,F(xiàn)擔(dān)任European Journal of Operational Research、Journal of Scheduling、Computers and Operations Research等期刊編委, 在Management Science、Operations Research、European Journal of Operational Research、Journal of Scheduling等國(guó)際頂級(jí)期刊發(fā)表論文150余篇。

 

摘要:

The majority of publications in the extensive literature on resource-constrained project scheduling focus on a static deterministic setting for which a so-called baseline schedule is computed prior to project execution. In the real world, however, a project may be subject to considerable uncertainty. During the actual execution of a project, the baseline schedule may indeed suffer from disruptive events causing the actually realized activity start times to deviate from the predicted baseline start times. This presentation focuses on the construction of optimal policies for the RCPSP with stochastic activity durations, meaning that an optimal baseline schedule is selected as well as all optimal continuations in case a disruption occurs in the baseline schedule or in an already adapted schedule. First, we will take a look at the general case and discuss two models that are capable of constructing ‘optimal’ policies in the sense that these are optimal within the set of schedules that are considered. Next, we will consider a serial project scheduling problem of at most four activities, where the durations of the activities can take on two possible durations. For that particular case, we will construct the real optimal policies and we will infer some rules that can be useful in order to construct better schedules for the general case such that the resulting ‘optimal policies’ are improved.

 


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