Bayesteh, Ali (2024) Agile-based optimized planning and scheduling methodology for multiple scattered projects. PhD thesis, University of Alberta, Canada.
Abstract
Abstract: 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 inn vative 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.
| Item Type: | Thesis (Doctoral) |
|---|---|
| Thesis advisor: | Lu, Ming |
| Uncontrolled Keywords: | agile project management; resource constrained multi-project planning; optimized resource allocation |
| Index terms: | resource allocation, resource utilization, planning process, crew productivity, contract condition, planning method, direct cost, heuristic, project management technique, savings, holistic approach, complex project, dissertation, project management, performance metric, mixed integer, scheduling, penalty, project scheduling, subjectivity, face, strategy, urban infrastructure, decision-making, methodology, variation, collaboration, construction project, resource constraint, body of knowledge, drainage, complexity, project planning |
| Subjects: | production management, research methods, human factors and perception, research dissemination and communication, knowledge management, site logistics, economic analysis, strategic project management, urban planning, psychology, operations research, operations management, contractual condition, project management theory and practice, performance measurement, contract structure, management, economics, infrastructure and transport systems, regulatory law, systems engineering, project controls, decision analysis, control systems, risk assessment, business, mathematical modelling, resource management |
| Topics: | Quality Management, Legal Issues, Risk Management, Project Management, Engineering Principles, Time Control, Contract Administration, Organizational Design, Site Management, Urban Studies, Governance, Research Practice, Information Management, Cost Management, Business Strategy |
| Descriptive scope: | 4 PCTA |
N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here