Production Scheduling with Due Windows - Yu, Shun Chi
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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…mehr

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Produktbeschreibung
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.
Autorenporträt
During early years, the author has experienced in the printed circuitboard industry, electrical connectors traders, touch panel manufacturing,international snack brands toy gifts manufacturing, power adapter manufacturing,LED light power plant. Depending on his perseverance and determination, theauthor gradually gained a PhD, then he decided to devote to academic educationindustry, from March 2015 as an assistant professor until nowadays, upholding moralinteriorization, achievement realization and theory erotizations, lookingforward to teaching students earnestly, and becoming a prolific author one day.