A Grouping Genetic Algorithm for the Intercell Scheduling Problem

Abstract

To solve intercell scheduling problem in industrial environments, heuristic rules are becoming popular due to the simplicity and efficiency. Grouping decisions in decision blocks is an efficient way to make the use of heuristic rules. A decision block generation algorithm based on grouping genetic algorithm (DBGA) is proposed in this paper. In DBGA, both the size and the constitution of each decision block are evolved together. Non-sequential entities are grouped into decision blocks and rules are assigned to decision blocks simultaneously. Comparative experiments are conducted with different structures of decision blocks. The results verify the effectiveness of DBGA.