Graves / Ringuest | Models & Methods for Project Selection | E-Book | sack.de
E-Book

E-Book, Englisch, Band 58, 193 Seiten, eBook

Reihe: International Series in Operations Research & Management Science

Graves / Ringuest Models & Methods for Project Selection

Concepts from Management Science, Finance and Information Technology
2003
ISBN: 978-1-4615-0280-7
Verlag: Springer US
Format: PDF
 Kopierschutz: 1 - PDF Watermark

Concepts from Management Science, Finance and Information Technology

E-Book, Englisch, Band 58, 193 Seiten, eBook

Reihe: International Series in Operations Research & Management Science

ISBN: 978-1-4615-0280-7
Verlag: Springer US
Format: PDF
 Kopierschutz: 1 - PDF Watermark

Models & Methods for Project Selection systematically examines in this book treatment the latest work in the field of project selection modeling. The models presented are drawn from mathematical programming, decision theory, and finance. These models are examined in two categorical streams: the management science stream and the financial model stream. The book describes the assumptions and limitations of each model and provides appropriate solution methodologies. Its organization follows three main themes:
*Criteria for Choice: Chapters 1-3 investigate the effect of the choice of optimization criteria on the results of the portfolio optimization problem. 
*Risk and Uncertainty: Chapters 4-7 deal with uncertainty in the project selection problem. 
*Non-Linearity and Interdependence: These chapters deal with problems of non-linearity and interdependence as they arise in the project selection problem. Chapters 8, 9 and 10 present solution methodologies, which can be used to solve these most general project selection models.
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Zielgruppe

Research

Autoren/Hrsg.

Graves, Samuel B.
Ringuest, Jeffrey L.

Weitere Infos & Material

Dedication. Preface.

1. The linear multiobjective project selection problem.

2. Evaluating competing investments.

3. The linear project selection problem: an alternative to net present value.

4. Choosing the best solution in a project selection problem with multiple objectives.

5. Evaluating a portfolio of project investments.

6. Conditional stochastic dominance in project portfolio selection.

7. Mean-gini analysis in project selection.

8. A sampling-based method for generating nondenominated solutions in stochastic MOMP problems.

9. An interactive multiobjective complex search for stochastic problems.

10. An evolutionary algorithm for project selection problems based on stochastic multiobjective linearly constrained optimization.

Index.

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