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<p>In this paper, we develop a method to obtain an ideal configuration of a steel factory scrapyard. The task must be accomplished using two rows of boxes for the storage of different materials, choosing between several possibilities in the loading order of each required mixture of those materials, and complying with a sequential production plan. Solutions are provided through three different phases, two using MILP models and another using a simulated annealing heuristic: the first finds an optimal split of the scrap types for the two rows, followed by obtaining the optimal box placement given a fixed order for each recipe, and finally an approach to find the best order to produce each recipe. As a result, we obtain <InlineEquation ID="IEq1"> <EquationSource Format="TEX">\({\textbf {10\%}}\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mn mathvariant="bold">10</mn> <mo>%</mo> </mrow> </math></EquationSource> </InlineEquation> reductions on processing times of a given production plan, when comparing a rule-of-thumb solution with a solution provided by our method. The impact of these improvements is not just related to time issues, since this reduction might also allow incorporating more demanding orders, with the corresponding benefits. Additionally, we analyze the influence of the production plan on the configuration of the layout.</p>

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Layout Optimization Model for Multi-recipe and Multi-route Problems with Application to the Design of a Steel Factory

  • 期刊论文

  • 发表日期：

    2026年1月7日

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  • Ricardo Enguiça,
  • Filipa Soares

摘要

In this paper, we develop a method to obtain an ideal configuration of a steel factory scrapyard. The task must be accomplished using two rows of boxes for the storage of different materials, choosing between several possibilities in the loading order of each required mixture of those materials, and complying with a sequential production plan. Solutions are provided through three different phases, two using MILP models and another using a simulated annealing heuristic: the first finds an optimal split of the scrap types for the two rows, followed by obtaining the optimal box placement given a fixed order for each recipe, and finally an approach to find the best order to produce each recipe. As a result, we obtain \({\textbf {10\%}}\) 10 % reductions on processing times of a given production plan, when comparing a rule-of-thumb solution with a solution provided by our method. The impact of these improvements is not just related to time issues, since this reduction might also allow incorporating more demanding orders, with the corresponding benefits. Additionally, we analyze the influence of the production plan on the configuration of the layout.