A study on DAA-based crane scheduling models for steel plant

Abstract

Crane scheduling tasks in steelworks are a matter of uncertainty scheduling with certain probability distribution pattern. To better schedule tasks with this feature, this paper proposes a Dynamic Area Allocation (DAA)-based crane scheduling model according to the following steps. First, Bayesian network, according to the time sequence of crane transportation tasks, is constructed. Then, conditional probability for each network node on the basis of actual crane operating data is calculated for getting the corresponding time–space probability distribution, and then obtaining the spatial distribution by superposing of all crane transportation tasks in the space domain at certain time. At last, tasks are assigned to cranes based on their spatial distribution and the equal probability partition. Simulation testing on the scheduling model is carried out using practical crane transportation tasks in steelworks. Results show that the model based on the dynamic area allocation, with its scheduling period of 15 min, can greatly shorten transportation time and reduce times of collision resulted from crane interference, after compared with the current widely used crane scheduling programme based on the fixed area allocation (FAA).