Production Scheduling with Due Windows
-Flow Shop and Job Shop Cases
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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 (W...
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.
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