With related studies demonstrating that ant colony optimization algorithm (ACO), and particle swarm algorithm (PSO) are both effective and efficient means of solving scheduling problems, this study, develops a farness particle swarm optimization algorithm (FPSO) to solve reentrant two-stage multiprocessor flow shop scheduling problems in order to minimize earliness and tardiness, a novel effective ant colony optimization (EACO) algorithm to solve two-stage flexible flow shop scheduling problems and thereby minimize earliness, tardiness and makespan, and a wise select ant colony optimization (WSACO) utilizing due window and sequence dependent setup time for constraints in job shop scheduling.