Ebook: Dynamic and Stochastic Multi-Project Planning

Introduces new analytical models for optimal multi-project management based on decision rules in dynamic-stochastic environments
Presents new insights into the structure of optimal policies
Describes extensive experimental investigations into the performance of well-known heuristics for multi-project scheduling in dynamic-stochastic environments
Introduces new approaches for high quality computing policies which outperform existing heuristic policies

This book deals with dynamic and stochastic methods for multi-project planning. Based on the idea of using queueing networks for the analysis of dynamic-stochastic multi-project environments this book addresses two problems: detailed scheduling of project activities, and integrated order acceptance and capacity planning. In an extensive simulation study, the book thoroughly investigates existing scheduling policies. To obtain optimal and near optimal scheduling policies new models and algorithms are proposed based on the theory of Markov decision processes and Approximate Dynamic programming. Then the book presents a new model for the effective computation of optimal policies based on a Markov decision process. Finally, the book provides insights into the structure of optimal policies.

Related Subjects: Project Management, Operation Research/Decision Theory, Operations Research, Management Science, Innovation/Technology Management, Production/Logistics/Supply Chain Management, Discrete Optimization