Application of a Genetic Algorithm in Crane Movement Scheduling

This paper develops an operator guidance system for an industrial process which involves scheduling ideas from manufacturing systems. The industrial process under study is the converter aisle in a copper smelter. Our objective is to increase throughput by improving utilization of the smelter’s resources. This paper partly addresses this objective by applying scheduling techniques to optimize the usage of the plant’s bridge cranes which supply material movement. As a benchmark process, a mathematical model for the cranes is developed with constraints allowing realistic simulation studies to be performed. Genetic algorithms are used to schedule the cranes’ optimal movement.