Modeling The Natural History of Secondary-Progressive Multiple Sclerosis: A New Modeling Approach Using Discrete Event Simulation

The natural history of secondary progressive multiple sclerosis.

BACKGROUND The onset of secondary progression is a pivotal event in the course of relapsing-remitting (RR) multiple sclerosis (MS). Patients with secondary progressive MS (SPMS) experience continuous worsening of symptoms independent of the occurrence of relapses. Possible risk factors associated with the onset of SPMS remain under investigated in natural history studies of MS disease course. ...

Modeling Continuous Flow with Discrete - Event Simulation

This paper describes the application of discrete event simulation to study continuous material flow. Logistics is an integrated part of most manufacturing companies. The purpose of this study is to determine the required logistics operations to allow continuous operations of a chemical manufacturing plant. The application has been used to provide critical decision support.

A JAVA-BASED FRAMEWORK FOR DISCRETE EVENT SIMULATION A framework for Discrete Event Simulation and MOdeling

The system presented bridges the gap between three different research areas: discrete event simulation, heuristic optimization methods and distributed systems technology. Its goal is to provide a framework which supports an efficient implementation of simulation optimization projects, including heuristic optimum seeking procedures and parallel execution of experiments. It is written completely ...

Modeling System Architecture and Resource Constraints Using Discrete-Event Simulation

Optimizing system resource utilization is a key design objective for system engineers in communications, electronics, and other industries. System resources such as processors, memory, or bandwidth on a communication bus are often shared by various components in the system. To understand the utilization of a shared resource, system engineers must do two things: identify constraints on the resou...

USMC inventory control using optimization modeling and discrete event simulation