论文信息 - A Comparison of Optimization Techniques for Integrated Manufacturing Planning and Scheduling

A Comparison of Optimization Techniques for Integrated Manufacturing Planning and Scheduling

We describe a comparison between Simulated Annealing (SA), Dispatch Rules (DR), and a Coevolutionary Distributed Genetic Algorithm (DGA) solving a random sample of integrated planning and scheduling (IPS) problems. We found that for a wide range of optimization criteria the DGA consistently outperformed SA and DR. The DGA finds 8–9 unique high quality solutions per run, whereas the other techniques find only one. On average, each DGA solution is 10–15% better than SA solutions and 30–35% better than DR solutions.

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