Optimization of attendee lists by using metaheuristics: A case study on symposium planning in a college

Combinatorial optimization problems are drawing more attention and rapidly developing research field ranging from industrial world to educational applications. Discrete forms of some metaheuristics can generate optimal solutions to such kind of problems. Case study reported in this paper uses discrete versions of the migrating birds optimization algorithm, the artificial bee colony algorithm and the genetic algorithm to solve given symposium session optimization problem. Optimal combinations of the attendee lists for symposium sessions were created by using these three algorithms. Optimized attendee lists provided balanced distributions of attendee to the sessions. Thus, large saloon requirements of symposium planners were minimized. Then, scope of the problem was extended hypothetically, and proposed methods were employed one more time in order to measure their performances on the extended problem. The results show that metaheuristic algorithms used in this paper can achieve good combinatorial optimizations on symposium session optimization problem even if big increases occur in problem dimension.