Optimization of task sequencing and allocation

Nowadays, software projects are no longer isolated but drive the business process of many non-IT companies. With the rise of AI applied in many industries, the problem of optimally scheduling tasks and allocating proper resources has significantly increased the challenge because of the diversity of tasks and stakeholders in the project. Due to the large volume and dynamic nature of the required information, manual optimization is typically error-prone and inefficient. Computer-aided techniques can overcome these issues but require a strict representation of the information often of an informal nature. In this project, we aim to deliver a computer-aided optimization solution. We formalize the underlying information and develop a simulation-based optimization technique. The results will elevate the project/resource planning maturity of the partner organization and, as a consequence, directly impact the time, cost, and quality of their projects.

Faculty Supervisor:

Eugene Syriani

Student:

Partner:

Banque Nationale du Canada

Discipline:

Computer science

Sector:

Finance and Insurance; Professional, scientific and technical services

University:

Université de Montréal

Program: