Supervisors
- Position
- Senior Research Associate
- Division / Faculty
- Faculty of Science
- Position
- Professor in Operations Research
- Division / Faculty
- Faculty of Science
Overview
Meta-heuristics are powerful search algorithms for solving intractable optimization problems. There are many population based approaches, like genetic algorithms, evolutionary algorithms, particle swarm, etc. but most of these have a static population size.
Viruses arise and attack populations periodically. They typically appear when populations become abundant. Viruses infect population members, and often reduce the number of individuals. Viruses create spaces for more individuals and balance competition.
The concept of viruses may be mimicked and could be a useful optimization paradigm.
Research activities
Develop a “virus search meta-heuristic algorithm”. Implement the algorithm in C++. Choose an intractable decision problem like flowshop/jobshop scheduling, travelling salesman, etc, and create test cases/instances. Solve these test cases, compare with evolutionary algorithm, simulated annealing, and report efficacy.
Outcomes
A new meta-heuristic algorithm.
Skills and experience
Operations Research, C++
Keywords
Contact
Contact the supervisor for more information.