Hicks C

Pongcharoen P

Xie W

In this paper, an Artificial Immune System Scheduling Tool (AISST) for production scheduling in the capital goods industry is proposed. Companies in this sector produce products with complex product structure in low volume on an engineer-to-order basis. Precedence relationships arising from product structure, operation precedence and finite capacity were considered. This AISST aims to simultaneously reduce work-in-process inventory and achieve on-time delivery. The approach was tested through four case studies that used data obtained from a collaborating company. The proposed tool was compared to previous Genetic Algorithm approaches. The results show that the AISST achieved satisfactory results for all the problems and the AISST achieved better results than previous tool with similar amounts of search. However, when problems become larger, the advantages of the AISST became smaller. The AISST required more computational time than the Genetic Algorithm approach

An artificial immune system scheduling tool for production scheduling in the capital goods industry

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