scholarly journals Decision Support System Applications for Scheduling in Professional Team Sport. The Team's Perspective

2021 ◽  
Vol 3 ◽  
Author(s):  
Xavier Schelling ◽  
Jose Fernández ◽  
Patrick Ward ◽  
Javier Fernández ◽  
Sam Robertson

Background: Periodization implies the systematic planning of training and competition with the goal of reaching the best possible performance in the most important competition. In team sports, this consists of finding a flight-and-practice schedule that maximizes the opportunities to perform the periodized contents (e.g., trips, practices, games, and days off). This process is conducted whilst considering known constraints (e.g., competitive schedule, roster availability, weather, especial events, holidays, or emotional effect of days away). The way a scheduling decision support system (DSS) leads users to make a decision should allow for flexibility, whilst minimizing users' confusion and facilitating the understanding of the recommendation given by the scheduling decision support system. Traditional approaches to solving scheduling problems use either simulation models, analytical models, heuristic approaches or a combination of these methods. When it comes to evaluate how the scheduling DSS is performing, three overarching aspects need to be reviewed: context satisfaction, process efficiency, and output quality. Appropriate training periodization and scheduling of trips and training sessions are critical for teams to optimize training and recovery processes in order to maximize health and performance. This article presents a methodological framework for designing decision-support systems for scheduling in professional team sports.

1994 ◽  
Vol 79 (2) ◽  
pp. 158-166 ◽  
Author(s):  
A.T.M. Aerts ◽  
A. Jansen ◽  
L. Klieb ◽  
C. Noorlander ◽  
G. Wolf

Author(s):  
Yizi Zhou ◽  
Anne Liret ◽  
Jiyin Liu ◽  
Emmanuel Ferreyra ◽  
Rupal Rana ◽  
...  

Author(s):  
Armando Cartenì

In this chapter attention is focused on the container terminal optimization problem, given that today most international cargo is transported through seaports and on containerized vessels. In this context, in order to manage a container terminal it is sometimes necessary to develop a Decision Support System (DSS). This chapter investigated the prediction reliability of container terminal simulation models (DSS), through a before and after analysis, taking advantage of some significant investment made by the Salerno Container Terminal (Italy) between 2003 and 2008. In particular, disaggregate and an aggregate simulation models implemented in 2003 were validated with a large set of data acquired in 2008 after some structural and functional terminal modifications. Through this analysis it was possible to study both the mathematical details required for model application and the field of application (prediction reliability) of the different simulation approaches implemented.


2014 ◽  
Vol 9 (1) ◽  
Author(s):  
OSCAR L. BARBOZA ◽  
ORLANDO BALDERAMA ◽  
LANIE ALEJANDRO

This study aimed to determine yield and production constraints of peanut inCagayan Valley using Decision Support System for Agrotechnology Transfer; analyze yieldgaps between simulated and actual yield, and provide decision support to optimizeproduction. Simulation results using CSM-CROPGRO sub-model of DSSAT showed thathighest potential yield is 2,267 kgs. / Hectare when planted in October 15 under rainfedcondition. Under non-stressed conditions in the dry season, the potential yield is 4,805 kgs./hectare planted in December 15. From 10 years of yield data, gap between farmer’s yieldcompared with rainfed potential ranges from 153 to 2,116 kgs./ hectare.  Low rates ofnitrogen application and pests and diseases were the factors causing yield gaps.  The DSSATprogram also captured the effect of prolonged drought in the last quarter of 2009 whichresulted to underestimated yield, and the effect of warm weather in 2004 which showedlowering of potential yield by 50%. Regional analysis of peanut yields showed that centraleastern part is more productive for rainfed conditions during the dry season; whereassouthern part including Quirino and Ifugao is more suitable to producing peanut during thewet season due to cooler temperature.Keywords: Agriculture, groundnut, potential and actual yield, simulation, climate change,Decision Support System for Agrotechnology Transfer, Philippines


2020 ◽  
Vol 1 (11) ◽  
pp. 55-66
Author(s):  
Angela A. Shvetsova ◽  
◽  
Anna V. Zviagintseva ◽  

In practical applications, the tasks of strategic planning are complex and require many variant calculations when studying various scenarios, which are characterized by significant uncertainty in the forecast estimates. In this regard, the use of a complex of various means of information and analytical support for the activities of analysts and experts is relevant. Within the framework of this question, an information and analytical decision support system is proposed, focused on automating computational procedures in strategic planning. The system is organized on the basis of the Statistica computing platform and includes the platform's software tools, developed macros for describing and presenting statistical and analytical models, as well as decision support modules. The capabilities of the system are shown by specific examples of establishing patterns of development of Russian regions and cities in the real sector of the economy. The corresponding generalized models characterizing the state and development of regions by seven specific indicators in the period from 2012 to 2018 and by four specific indicators characterizing the development of cities in the period from 2003 to 2017 are obtained. It is established that the obtained models of collective behavior, presented in the form of equations of state, do not depend on time, but are determined only by the values of the achieved indicators. The proposed system allows you to increase the efficiency of the decisionmaking process, reduce the time and cost of developing strategic planning documents


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