|Ph.D Student||Cohen Izack|
|Subject||Management of Multi-Project Systems in Stochastic|
|Department||Department of Industrial Engineering and Management||Supervisors||Professor Avraham Shtub|
|Professor Boaz Golany|
This thesis suggests an approach that can enable multi-project organizations to improve their decision making process by taking into consideration the stochastic nature of the environment. Moreover, a framework is proposed to guide the selection of the solution approach to a specific problem. By using this framework this thesis addresses the 3 levels of decision making (strategic, tactical and operational) which are relevant to multi-project environments: 1) the stochastic version of the time-cost tradeoff problem has received little attention in the literature despite its relevancy in multi-project programs. This thesis provides a solution to this problem, which may be used for strategic budgeting decisions. 2) Two tactical-level issues are addressed: the number of projects that should be processed concurrently and intermediate-term resource allocation. 3) The operational management of on-going projects has not been quantitatively investigated for some of the popular multi-project management approaches. This thesis studies the performance of some of these approaches under different operating conditions and compares them.
State of the art methodologies are used for the modeling and the optimization of the discussed multi-project environments (for example, Process Management, Cross Entropy and Robust Optimization). Unique solution approaches are developed, using these methodologies, to address different management problems such as: the stochastic, continuous time-cost tradeoff problem, the tactical resource allocation problem and the finite-capacity loading of projects. Additionally, new insights are provided for the operational management of multi-project environments.
Finally, future research directions are identified that would serve to improve and extend the use of the suggested approach.