A comparative study of meta-heuristics for identical parallel machines

This paper considers the scheduling problem of minimizing the weighted number of early and tardy jobs on identical parallel machines, Pm||∑wj(Uj + Vj). This problem is known to be NP complete and finding an optimal solution is unlikely. Six meta-heuristics including hybrids are proposed for solving the problem. The meta-heuristics considered are genetic algorithm, particle swarm optimization and simulated annealing with their hybrids. A comparative study that involves computational experiments and statistical analysis are presented evaluating these algorithms. The results of the research are very promising.