Ship-unloading scheduling optimization for a steel plant

A ship-unloading scheduling problem (SUSP), also called “sequencing ship” problem arising from a large steel plant with bulk material port is studied in this paper. Raw materials such as iron ore, coal and stone are transported to the steel plant by ships. Each ship has an expected departure time based on a contract between the steel plant and ship-owner. If the steel plant cannot effectively schedule the unloading operation of the ship to make it leave the port before its expected departure time, a demurrage penalty cost which increases with the delay will be charged to the steel plant by the ship-owner. SUSP is to find an optimal schedule for these raw material ships so as to minimize the total demurrage costs within a given planning time horizon. The problem is formulated as a mixed integer programming, and can be regarded as a flexible job shop scheduling problem, where the ships are regarded as the jobs and the belt conveyors as the machines. A column generation approach is proposed for solving the optimization model. The computational results on the real-world data obtained from the steel plant are compared with CPLEX to verify the effectiveness and merits of the proposed model and solution. The proposed optimization technique has great potential to be applied in the steel plant, and it may save 20 million of CNY caused by the delay cost per year.