Agile-Based Optimized Planning and Scheduling Methodology for Multiple Scattered Projects

• Author / Creator

  Bayesteh, Ali

• Effective project planning involves complex procedures crucial to project management's success. Resource allocation and project scheduling are at the core of these planning processes, which require careful attention to project and resource constraints. Allocating resources can be daunting, especially when resources are limited and must be shared among multiple projects. The scheduling of projects can compound this challenge, especially when projects have strict deadlines, are geographically dispersed, and require extensive preparation. Urban infrastructure construction and public/private utility companies face this challenge as they are responsible for the timely completion of many geographically dispersed construction projects with limited resources available. Implementing effective planning methods in such a dynamic resource constrained multi-project setting is paramount to avoid potential roadblocks from derailing the projects. Nonetheless, there is currently a lack of established methodologies that can effectively tackle the challenges inherent in this problem. The current project management techniques and scheduling methods fall short in their ability to explicitly state, model, analyze, and optimize the problem of resource allocation and scheduling multiple concurrent projects. Therefore, this dissertation explores the problem and offers an academic and practical methodology to tackle this significant industry challenge through collaboration with Epcor Drainage Construction Services.
  This research makes academic contributions by clearly and effectively defining a short-term planning problem in a multi-project management domain with dynamic constraints on project information, resource availability, and contractual obligations (penalty/cancel charges), merges agile project management and optimization as a novel solution to the problem, proposes an innovative agile-based framework tailored to the context of the problem to govern the planning process at the level of the projects, and develops advanced simplified mixed integer linear (MIP) and binary (0-1) models to enhance the optimization process without compromising the complexity of the problem. The developed models contribute to the body of knowledge by transforming many "If-Then" conditions conceived from the problem's combinatorial nature and incorporating commonly applicable project terms and contract conditions in the real world. This feature makes optimization more efficient and expeditious, catalyzing agile project management. Performance metrics are devised to evaluate the goodness of the resultant plans, and a heuristic algorithm, based on a generalized representation of the current industry practice, is developed for validating the model outcomes. Additionally, the uncertainties inherent in the multi-project environment of the problem are thoroughly explored, and a creative management approach to address uncertainties is proposed as a valuable addition to the holistic approach undertaken by the research. Finally, a novel analytical method is proposed to address underlying issues with the subjectivity of expert opinions and quantify the results in a Multi-Criteria Decision Making (MCDM) application, which is applied to model the crew productivity in this research. This method is an additional contribution and adds value to the research, especially when dealing with the lack of adequate data to account for crew productivity variation.
  The practical research outcomes yield direct cost savings in the industry by planning for more projects, maximizing resource utilization and work continuity, preventing or minimizing delay penalties, and eliminating cancellation charges. Furthermore, it reduces the application cost of optimization by using cost-effective optimization engines to find solutions in line with the agile project management framework. The cutting-edge methods established in this research can be adapted to facilitate the time-sensitive dispatching of finite crew resources to multiple projects across various sectors. The insights and innovative solutions presented in this dissertation have the potential to yield significant benefits for both academic and industry communities. Ultimately, this work contributes to a deeper understanding of complex project management challenges and enables organizations to develop more effective project management strategies and methods.

• Subjects / Keywords

  • Agile Project Management
  • Resource Constrained Multi-Project Planning
  • Optimized Resource Allocation

• Graduation date

  Spring 2024

• Type of Item

  Thesis

• Degree

  Doctor of Philosophy

• DOI

  https://doi.org/10.7939/r3-sywn-m748

• License

  This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.