Using simulated annealing and ant-colony optimization algorithms to solve the scheduling problem

Abstract

The scheduling problem is one of the most challenging problems faced in many different areas of everyday life. This problem can be formulated as a combinatorial optimization problem, and it has been solved with various methods using heuristics and intelligent algorithms. We present in this research an efficient solution to the scheduling problem using two different heuristics namely Simulated Annealing and Ant Colony Optimization. A study comparing the performances of both solutions is described and the results are analyzed.