An Artificial Hormone-Based Algorithm For Production Scheduling From The Bottom-Up

This paper presents a model for supporting a production scheduling system with an artificial hormone algorithm. The system consists of lots that have to undergo a number of processing steps on different machines. The processing steps for a lot are formalized in a recipe assigned to the lot type. Since the steps in the recipe have to be processed in order, the given system allows choice only in the context of selecting a particular machine for the next step and in changing the processing order of waiting lots at a machine. Optimization of such a job-shop scheduling system is an NP-hard problem. In the approach proposed by this paper, artificial hormone systems are used to express the urgency of a lot and the need for new lots at a machine type, thus providing a system using local information for optimization. Results indicate that the artificial hormone system provides an improvement of around 5% over a First Come-First Serve approach.