  This research is focused on solving problems in the area of software project
management using metaheuristic search algorithms and as such is research in the
field of search based software engineering. The main aim of this research is to
evaluate the performance of different metaheuristic search techniques in
resource allocation and scheduling problems that would be typical of software
development projects. This paper reports a set of experiments which evaluate
the performance of three algorithms, namely simulated annealing, tabu search
and genetic algorithms. The experimental results indicate that all of the
metaheuristics search techniques can be used to solve problems in resource
allocation and scheduling within a software project. Finally, a comparative
analysis suggests that overall the genetic algorithm had performed better than
simulated annealing and tabu search.
