A Swarm Intelligence Method Applied to Manufacturing Scheduling

In this paper we present a multi-agent search technique to face the NP-hard single machine total weighted tardiness scheduling problem in presence of sequence-dependent setup times. The search technique is called Discrete Particle Swarm Optimization (DPSO): differently from previous approaches the proposed DPSO uses a discrete model both for particle position and velocity and a coherent sequence metric. We tested the proposed DPSO over a benchmark available online. The results obtained show the competitiveness of our DPSO, which is able to outperform the best known results for the benchmark, and the effectiveness of the DPSO swarm intelligence mechanisms.

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