scholarly journals MAXIMIZING THE PROFITABILITY ON INVESTMENT BY OPTIMIZING THE PRODUCTION PROGRAM

2021 ◽  
Vol 2021 (4) ◽  
pp. 4913-4917
Author(s):  
JAROSLAVA KADAROVA ◽  
◽  
JAROSLAVA JANEKOVA ◽  
DANIELA ONOFREJOVA ◽  
◽  
...  
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Economic Efficiency ◽  
Production Capacity ◽  
Investment Decisions ◽  
Corporate Investment ◽  
Business Investment ◽  
Production Program ◽  
Future Production ◽  
Fixed Assets

Investments in tangible fixed assets significantly affect the future production capacity of the company, they are a stimulator of the company's development. At the same time, they are associated with a degree of uncertainty that needs to be taken into account when making investment decisions. The article presents an approach to optimizing inhomogeneous production in order to maximize the economic efficiency of a particular business investment. The economic efficiency of the investment is assessed comprehensively in terms of profitability, liquidity and risk. The risk is addressed through Monte Carlo simulation and the production program is optimized using OptQuest. The result is a production program that maximizes the return on the assessed corporate investment.

Using Monte Carlo Simulation to Improve Ceramic R&D Investment Decisions

2010 ◽  
Vol 105-106 ◽  
pp. 798-801
Author(s):  
Bao Cheng He ◽  
Hong Tao Jiang ◽  
Shu Zhi Yao ◽  
Bao Yuan He
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Real Options ◽  
Cash Flow ◽  
Investment Decisions ◽  
Discounted Cash Flow ◽  
Valuation Model ◽  
Managerial Flexibility ◽  
D Investment

The success of ceramic companies is highly dependent on research and development (R&D). Thus, a pivotal aim of management is to allocate resources to the best scientific and financial R&D projects. But the valuation of ceramic R&D is a difficult task for managers. The conventional discounted cash flow (DCF) methods fail to consider the value of managerial flexibility provided by R&D projects. Real options Analysis (ROA) offers a superior way of capturing the value of flexibility. It enables decision-maker to value projects more accurately by incorporating managerial flexibilities into the valuation model. However, ROA can’t effectively deal with the volatility of parameters in itself under high uncertain circumstance. In view of the limitation of ROA, this paper uses Monte Carlo simulation to solve the parameters volatility problems. In the end, the case study proves that Monte Carlo simulation can improve R&D investment decisions, especially for highly unpredictable ceramic R&D projects.

Investment Decisions Based on the Postponed Options PROT Hydropower Project

2014 ◽  
Vol 672-674 ◽  
pp. 2098-2105
Author(s):  
Jun Xin Shen ◽  
Xiao Jun Guo
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Investment Decisions ◽  
Current Method ◽  
Simulation Method ◽  
Decision Makers ◽  
Monte Carlo Simulation Method ◽  
Hydropower Project ◽  
Project Investment ◽  
Project Valuation

The analysis and description of the current method used in hydropower project investment decisions and problems of the introduction of the Monte Carlo simulation method PROT hydropower project valuation. Examples of analysis results showed that: this method can better reflect the actual value of the uncertainty of hydropower projects, flexibility and projects to provide a reasonable basis for decision makers.

Electron Scattering in Solids

1990 ◽  
Vol 48 (2) ◽  
pp. 4-5
Author(s):  
Ryuichi Shimizu ◽  
Ze-Jun Ding
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Angular Distribution ◽  
Elastic Scattering ◽  
Electron Scattering ◽  
Cross Sections ◽  
Expansion Method ◽  
Electron Excitation ◽  
Partial Wave Expansion ◽  
Backscattered Electrons

Monte Carlo simulation has been becoming most powerful tool to describe the electron scattering in solids, leading to more comprehensive understanding of the complicated mechanism of generation of various types of signals for microbeam analysis.The present paper proposes a practical model for the Monte Carlo simulation of scattering processes of a penetrating electron and the generation of the slow secondaries in solids. The model is based on the combined use of Gryzinski’s inner-shell electron excitation function and the dielectric function for taking into account the valence electron contribution in inelastic scattering processes, while the cross-sections derived by partial wave expansion method are used for describing elastic scattering processes. An improvement of the use of this elastic scattering cross-section can be seen in the success to describe the anisotropy of angular distribution of elastically backscattered electrons from Au in low energy region, shown in Fig.l. Fig.l(a) shows the elastic cross-sections of 600 eV electron for single Au-atom, clearly indicating that the angular distribution is no more smooth as expected from Rutherford scattering formula, but has the socalled lobes appearing at the large scattering angle.

Determination of Stoichiometry of GaAs Component in (Gaas)Ge Epitaxially Grown Thin Films by Electron Microprobe X-Ray Analysis

1990 ◽  
Vol 48 (2) ◽  
pp. 264-265
Author(s):  
D. R. Liu ◽  
S. S. Shinozaki ◽  
R. J. Baird
Keyword(s):  
Thin Film ◽  
Thin Films ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Compound Semiconductors ◽  
Energy Dispersive Analysis ◽  
X Ray ◽  
Metastable Alloys ◽  
Lower Voltage

The epitaxially grown (GaAs)Ge thin film has been arousing much interest because it is one of metastable alloys of III-V compound semiconductors with germanium and a possible candidate in optoelectronic applications. It is important to be able to accurately determine the composition of the film, particularly whether or not the GaAs component is in stoichiometry, but x-ray energy dispersive analysis (EDS) cannot meet this need. The thickness of the film is usually about 0.5-1.5 μm. If Kα peaks are used for quantification, the accelerating voltage must be more than 10 kV in order for these peaks to be excited. Under this voltage, the generation depth of x-ray photons approaches 1 μm, as evidenced by a Monte Carlo simulation and actual x-ray intensity measurement as discussed below. If a lower voltage is used to reduce the generation depth, their L peaks have to be used. But these L peaks actually are merged as one big hump simply because the atomic numbers of these three elements are relatively small and close together, and the EDS energy resolution is limited.

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