Multi-project scheduling is a complex coordination of different resources (i.e. workforce, machines, materials, budgets) in real time and most of the studies are based on limited assumptions€”such as each project in a multi-project scheduling is treated as a single project scheduling problem, or simplistically that resources can be transferred between projects without expense and time, or that projects can run without any uncertainties (i.e. under ideal settings). However, in practice, while scheduling the activities of multiple projects in dynamic environments, project managers face challenges that are typically due to the lack of timely, accurate, and consistent information; finite resource transfer times (that may also have uncertainties), interdependencies among activities of different projects; and uncertain activity interruptions. Consequently, existing theoretical approaches strategies are not useful in practice and it is challenging to solve the practical multi-project scheduling proble

To minimise this gap, this work aims at developing a decision support system for multi-project scheduling problem using the internet of things (IoT) concept. Under the Internet of Manufacturing Things, real-time status of each project activity and the status of the resources can be monitored. Based on the captured information, a mathematical model will be developed to achieve profit maximisation and energy minimisation as objectives. Efficient algorithms-based decision support systems (i.e. exact, heuristics, or a combination of both) will be developed to find the optimal or near-optimal solutions in of activity sequence of activities of each project and schedule of resources, i.e. when and where the resources will be used by which activity. In addition, the solution techniques will consider uncertainties and project plan will be rescheduled. Outcomes of this study should be useful for the project managers in managing multiple projects more cost-effectively.

Research Aim:

  • study existing approaches available in both single and multi-project scheduling problems
  • study real life projects from software development to ship building and identify challenges and develop models considering realistic objective functions and constraints in IoT environments
  • the model is expected to be solved by developing exact and heuristics scheduling and re-scheduling techniques and verifying their performances by solving realistic instances
  • solving real-life project scheduling problem will be the final stage of this project.

Contact:

Contact Dr Humyun Fuad Rahman md.rahman@unsw.edu.au or Dr Ripon Chakrabortty r.chakrabortty@adfa.edu.au for further information. Each potential student needs to write a research proposal highlighting research motivation, research problems, research objectives, brief review of the most relevant literature, proposed methodology and expected outcome.

School

School of Engineering & IT

Research Area

Technology Decision Making | Optimization & Design | Project Management

Supervisor

PG Project Management, Decision Analytics, and Engineering Science Program Coordinator & Lecturer - Systems Engineering & Decision Analytics Ripon Chakrabortty
PG Project Management, Decision Analytics, and Engineering Science Program Coordinator & Lecturer - Systems Engineering & Decision Analytics