Stochastic Models in Graded Manpower systems

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Modeling is a simplified representation of reality. Deterministic models provide exact or consistent prediction for every variable. Stochastic modeling concerns the use of probability to model real-world situations in which uncertainty is present. Since uncertainty is pervasive, this means that the tools of this stochastic process can potentially prove useful in almost all facets of professional life and sometimes even in personal life as in gambling, personal finances economic forecasting, product demand, call center provisioning, product reliability and warranty analysis. Planning is an inevitable phenomenon in everyday life and stochastic modeling can help to maximize use of available manpower, finance and material resources. The Monte Carlo Simulation is an example of a stochastic model used in finance. Stochastic modeling is a practical tool for predicting employer and employee behavior and manpower stocks and flows based on rational assumptions. Models discussed in this book certainly build a strong base for students and researchers from business, industry, computer science, management studies and allied areas who seek the knowledge in applied stochastic processes.

Autorentext

Srinivasa Rao Vatluri, is a Professor & University Head with 15 years of Teaching and Research Experience in Acharya NG Ranga Agricultural University, India. Expertise in Stochastic Process and Design of Experiments and guided more than 200 M.Sc (Ag.) and Ph.D students. Statistical consultant, SAS Nodal Officer and contributed more than 150 papers.

Weitere Informationen

  • Allgemeine Informationen
    • GTIN 09783659439575
    • Sprache Englisch
    • Größe H220mm x B150mm x T9mm
    • Jahr 2013
    • EAN 9783659439575
    • Format Kartonierter Einband
    • ISBN 3659439576
    • Veröffentlichung 15.08.2013
    • Titel Stochastic Models in Graded Manpower systems
    • Autor Srinivasa Rao Vatluri
    • Gewicht 238g
    • Herausgeber LAP LAMBERT Academic Publishing
    • Anzahl Seiten 148
    • Genre Mathematik

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