Utilizing Discrete Event Simulation for Schedule Analysis: Processes and Lessons Learned from NASA's GOPD Integrated Timeline Model

2015 ◽  
Vol 8 (1) ◽  
pp. 55-59
Author(s):  
Angelo C. Conner ◽  
Luis Rabelo
Keyword(s):  
Discrete Event Simulation ◽  
Discrete Event ◽  
Lessons Learned ◽  
Event Simulation

COMPUTER SIMULATION SOFTWARE REUSE BY GENERIC/SPECIFIC DOMAIN MODELING APPROACH

1994 ◽  
Vol 04 (01) ◽  
pp. 81-102 ◽  
Author(s):  
CHUNG-HORNG LUNG ◽  
JEFFERY K. COCHRAN ◽  
GERALD T. MACKULAK ◽  
JOSEPH E. URBAN
Keyword(s):  
Discrete Event Simulation ◽  
Software Reuse ◽  
Discrete Event ◽  
Domain Analysis ◽  
Simulation Software ◽  
Lessons Learned ◽  
Domain Modeling ◽  
Specific Approach ◽  
Event Simulation ◽  
Modeling Approach

Software reuse has drawn much attention in computing research. Domain analysis is considered a prerequisite to effective reuse of existing software. Several approaches and methodologies have been proposed for domain analysis or domain modeling, but not many case studies have been reported in the literature. The first objective of this paper is to present the concept and practical experiences of a domain analysis approach in discrete-event simulation in manufacturing — generic /specific modeling. A second objective of this paper is to present a meta-model based on the generic/ specific approach from the software engineering perspective. The steps and knowledge required to build the model are described. Domain analysis lessons learned from the generic/specific approach in discrete-event simulation are discussed. Classification of this domain modeling approach was conducted through the Wartik and Prieto-Diaz criteria. The classification will facilitate the comparison with other domain analysis approaches. Similar modeling concepts or techniques may be beneficial to other researchers in their own application domains.

Managing funerary systems in the pandemic: lessons learned and an application of a scenario simulation in São Paulo City, Brazil

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Irineu de Brito Jr ◽  
Manoel Henrique Capistrano Cunha ◽  
Luiz Antonio Tozi ◽  
Luiz Augusto Franzese ◽  
Márcia Lorena da Silva Frazão ◽  
...  
Keyword(s):  
Decision Making ◽  
Discrete Event Simulation ◽  
Discrete Event ◽  
Sao Paulo ◽  
Lessons Learned ◽  
São Paulo ◽  
Content Type ◽  
Event Simulation ◽  
Discrete Event Simulation Model ◽  
The City

PurposeThis study, a practice forum article, aims to presents the lessons learned and the development of a discrete event simulation model to support the funerary system management of São Paulo City, Brazil, during the COVID-19 pandemic.Design/methodology/approachA discrete event simulation model was developed by the authors as soon as the pandemic affected the city of São Paulo, Brazil. Based on the model, several scenarios with varying minimum, median and peak demands (i.e. the number of deaths) were tested and evaluated. The lessons learned from the scenario analysis and implementation of the decision-making of the city government of São Paulo are discussed in this article.FindingsThe lessons learned about the coordination, inventory management and other operational characteristics in funerary logistics during the pandemic are shared with a model, which quantifies the demand for vehicles, coffins, graves and teams in the cemeteries in different simulated scenarios.Practical implicationsThe São Paulo State Civil Defense used this information during the pandemic to prepare the funerary system of the municipality.Social implicationsThe study presents methods to mitigate the sanitary, environmental and psychosocial problems related to the funerary system.Originality/valueStudies on funerary systems are scarce. This study presents the results that supported the dimensioning of the funerary system during the pandemic and operational lessons about the logistics to support decision-making in future events.

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