Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: There are several techniques for estimating cost and time for software development. These are known in software engineering as "software metrics." LOC (lines of code), COCOMO (COnstructive COst Model), and FPA (Function Point Analysis) are examples of such techniques. Although Discrete Event Simulation Modeling (DESM) has some differences from classical software development, it is possible to draw a parallel beten these techniques and DESM. This article reviews some of the metrics from software engineering, and, based on those, proposes a metric for estimating time for the implementation of a simulation model using one specific simulation software. The results obtained for 22 real simulation projects shod that the proposed technique can estimate the time for software development with acceptable accuracy (average error of 6% and maximum absolute error of 38%) for models that have less that 200 simulation objects.
['Leonardo Chwif', 'Jerry Banks', 'Marcos Ribeiro Pereira Barretto']
I am writing a research paper on a idea Estimating the implementation time for discrete-event simulation model building
[{"from": "human", "value": "I am writing a research paper on a idea Estimating the implementation time for discrete-event simulation model building"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: There are several techniques for estimating cost and time for software development. These are known in software engineering as \"software metrics.\" LOC (lines of code), COCOMO (COnstructive COst Model), and FPA (Function Point Analysis) are examples of such techniques. Although Discrete Event Simulation Modeling (DESM) has some differences from classical software development, it is possible to draw a parallel beten these techniques and DESM. This article reviews some of the metrics from software engineering, and, based on those, proposes a metric for estimating time for the implementation of a simulation model using one specific simulation software. The results obtained for 22 real simulation projects shod that the proposed technique can estimate the time for software development with acceptable accuracy (average error of 6% and maximum absolute error of 38%) for models that have less that 200 simulation objects."}]