Buch, Englisch, 193 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 330 g
Reihe: International Series in Operations Research & Management Science
Concepts from Management Science, Finance and Information Technology
Buch, Englisch, 193 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 330 g
Reihe: International Series in Operations Research & Management Science
ISBN: 978-1-4613-5001-9
Verlag: Springer US
*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.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Wirtschaftswissenschaften Betriebswirtschaft Management Forschung & Entwicklung (F&E), Innovation
- Wirtschaftswissenschaften Betriebswirtschaft Unternehmensforschung
- Wirtschaftswissenschaften Finanzsektor & Finanzdienstleistungen Finanzsektor & Finanzdienstleistungen: Allgemeines
- Wirtschaftswissenschaften Betriebswirtschaft Management Entscheidungsfindung
Weitere Infos & Material
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 Nondominated 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.