Mathematical modeling is one of the key methodologies of metabolic engineering. Based on a given metabolic model different computational tools for the simulation, data evaluation, systems analysis, prediction, design and optimization of metabolic systems have been developed. The currently used metabolic modeling approaches can be subdivided into structural models, stoichiometric models, carbon ...

Dow AgroSciences has improved its bottom line by using simulation-based optimization to reduce the time and expense of moving a portfolio of products to market. We examined mathematical programming approaches for scheduling new-product development but found that the solution of these formulations is intractable for problems of practical size that include resource constraints. We developed a sim...

Title of Document: SIMULATION AND OPTIMIZATION OF PRODUCTION CONTROL FOR LEAN MANUFACTURING TRANSITION Sean M. Gahagan, Ph.D., 2008 Directed By: Associate Professor Jeffrey W. Herrmann, Department of Mechanical Engineering Lean manufacturing is an operations management philosophy that advocates eliminating waste, including work-in-process (WIP) inventory. A common mechanism for controlling WIP ...

Game designers can use computer-aided game design methods to quantitatively compare player skill levels, different game variants, and learning rates, for the purpose of modeling how players will likely experience a game. We use Monte-Carlo simulation, hazard functions, and survival analysis to show how difficulty will quantitatively change throughout a game level as we vary skill, game paramete...

‎Mathematical models are the most important tools in epidemiology to understand previous outbreaks of diseases and to better understand the dynamics of how infections spread through populations‎. ‎Many existing models closely approximate historical disease patterns‎. ‎This article investigates the mathematical model of the deadly disease with severe and uncontrollable bleeding‎, ‎Ebola which is...

Optimal Reactive Power Dispatch (ORPD) is a multi-variable problem with nonlinear constraints and continuous/discrete decision variables. Due to the stochastic behavior of loads, the ORPD requires a probabilistic mathematical model. In this paper, Monte Carlo Simulation (MCS) is used for modeling of load uncertainties in the ORPD problem. The problem is formulated as a nonlinear constrained mul...

Assembly line balancing is the problem of assigning tasks to workstations by optimizing a performance measure while satisfying precedence relations between tasks and cycle time restrictions. Many exact, heuristic and metaheuristic approaches have been proposed for solving simple straight and U-shaped assembly line balancing problems. In this study, a quite new optimization algorithm, Bacterial ...

Abstract: A three-phase to single-phase matrix converter is investigated in the present paper. Based on the state matrix vector, a mathematical analysis of the converter is performed giving the relation between the sinusoidal line voltage (current) and the output voltage (current). The results of the investigation are confirmed using computer simulation of the converter by the program product C...

This study formulates the effects of two different historical data types on electrical energy consumption of ASEAN-5 counties. On this basis, optimized GEP (gene expression programming) is applied to precisely formulate the relationships between historical data and electricity consumption. The optimized GEP is a more recent extension of GEP with high probability of finding closed-form solution ...