An Air-Ground Cooperative Scheduling Model Considering Traffic Environment and Helicopter Performance

2021 ◽  
pp. 107458
Author(s):  
Ming Zhang ◽  
Songrui Li ◽  
Boquan Li
Keyword(s):  
Scheduling Model ◽  
Traffic Environment ◽  
Cooperative Scheduling

A Cooperative Scheduling Model for Timetable Optimization in Subway Systems

2013 ◽  
Vol 14 (1) ◽  
pp. 438-447 ◽  
Author(s):  
Xin Yang ◽  
Xiang Li ◽  
Ziyou Gao ◽  
Hongwei Wang ◽  
Tao Tang
Keyword(s):  
Scheduling Model ◽  
Cooperative Scheduling ◽  
Timetable Optimization

scholarly journals Operating Rooms efficiency: leveraging data to improve management of elective surgery

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
C Quercioli ◽  
G A Carta ◽  
G Cevenini ◽  
G Messina ◽  
N Nante ◽  
...  
Keyword(s):  
Historical Data ◽  
Elective Surgery ◽  
District General Hospital ◽  
Operating Rooms ◽  
Accurate Estimation ◽  
Surgical Time ◽  
Accurate Analysis ◽  
Management Efficiency ◽  
Scheduling Model ◽  
The Mean

Abstract Background Careful scheduling of elective surgery Operating Rooms (ORs) is crucial for their efficient use, to avoid low/over utilization and staff overtime. Accurate estimation of procedures duration is essential to improve ORs scheduling. Therefore analysis of historical data about surgical times is fundamental to ORs management. We analyzed the effect, in a real setting, of an ORs scheduling model based on estimated optimum surgical time in improving ORs efficiency and decreasing the risk of overtime. Methods We studied all the 2014-2019 elective surgery sessions (3,758 sessions, 12,449 interventions) of a district general hospital in Siena's Province, Italy. The hospital had3 ORs open 5 days/week 08:00-14:00. Surgery specialties were general surgery, orthopedics, gynecology and urology. Based on a pilot study conducted in 2016, which estimated a 5 times greater risk of having an OR overtime for sessions with a surgical time (incision-suture)>200 minutes, from 2017 all the ORs were scheduled using a maximum surgical time of 200 minutes calculated summing the mean surgical times for intervention and surgeon (obtained from 2014-2016 data). We carried out multivariate logistic regression to calculate the probability of ORs overtime (of 15 and 30 minutes) for the periods 2014-2016 and 2017-2019adjusting for raw ORs utilization. Results The 2017-2019 risk of an OR overtime of 15 minutes decreased by 25% compared to the 2014-2016 period (OR = 0.75, 95%CI=0.618-0.902, p = 0.003); the risk of a OR overtime of 30 minutes decreased by 33% (OR = 0.67, 95%CI= 0.543-0.831, p < 0.001). Mean raw OR utilization increase from 62% to 66% (p < 0.001). Mean number of interventions per surgery sessions increased from 3.1 to 3.5 (p < 0.001). Conclusions This study has shown that an analysis of historical data and an estimate of the optimal surgical time per surgical session could be helpful to avoid both a low and excessive use of the ORs and therefore to increase the efficiency of the ORs. Key messages An accurate analysis of surgical procedures duration is crucial to optimize operating room utilization. A data-based approach can improve OR management efficiency without extra resources.

scholarly journals Short-Term Scheduling Model of Cluster Tool in Wafer Fabrication

Mathematics ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 1029
Author(s):  
Ying-Mei Tu
Keyword(s):  
Arrival Time ◽  
Time Estimation ◽  
Advanced Technology ◽  
Shop Floor ◽  
Process Time ◽  
Short Term ◽  
Work In Process ◽  
Scheduling Model ◽  
Cluster Tools ◽  
Cluster Tool

Since last decade, the cluster tool has been mainstream in modern semiconductor manufacturing factories. In general, the cluster tool occupies 60% to 70% of production machines for advanced technology factories. The most characteristic feature of this kind of equipment is to integrate the relevant processes into one single machine to reduce wafer transportation time and prevent wafer contaminations as well. Nevertheless, cluster tools also increase the difficulty of production planning significantly, particularly for shop floor control due to complicated machine configurations. The main objective of this study is to propose a short-term scheduling model. The noteworthy goal of scheduling is to maximize the throughput within time constraints. There are two modules included in this scheduling model—arrival time estimation and short-term scheduling. The concept of the dynamic cycle time of the product’s step is applied to estimate the arrival time of the work in process (WIP) in front of machine. Furthermore, in order to avoid violating the time constraint of the WIP, an algorithm to calculate the latest time of the WIP to process on the machine is developed. Based on the latest process time of the WIP and the combination efficiency table, the production schedule of the cluster tools can be re-arranged to fulfill the production goal. The scheduling process will be renewed every three hours to make sure of the effectiveness and good performance of the schedule.

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