Abstract
The material handling process is critical in steel enterprises’ raw material supply chain. A well-designed material handling model and scheduling scheme can significantly enhance the supply of raw materials, improve steel production efficiency, reduce operational and management costs, and facilitate scientific management practices. This article presents a multi-objective optimisation model for the stacker-reclaimer machine, targeting the total transportation time and equipment utilisation balance rate during a single operational planning period within the raw material yard. To tackle the complex challenge of material handling scheduling, we introduce the Multi-objective Indirect Optimisation Non-Dominated Sorting Genetic Algorithm II, which utilises an indirect optimisation approach to effectively manage many objectives and constraints while enhancing the convergence speed towards the Pareto optimal front. Moreover, the model incorporates the influence of the repose angle of the material pile on handling efficiency, optimising the operational angles and paths of the stacker reclaimer. Ultimately, through a simulation case study from a small steel plant in Xiangtan, Hunan, we demonstrate that the scheduling scheme derived from the optimal Pareto solution reduces the maximum completion time by 8.76 min compared to the actual scheduling scheme while also achieving a 3.46% increase in the equipment utilisation balance rate. This confirms that our proposed method successfully balances transportation time and equipment utilisation. Additionally, an emergency scheduling analysis of the stacker reclaimer at a large port further corroborates the speed and accuracy of the multi-objective indirect optimisation algorithm, providing a valuable reference for optimising scheduling in steel enterprises and ensuring the quality of raw material supply.
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