求解具有時(shí)空約束的板坯庫天車調(diào)度問題Memetic算法
發(fā)布時(shí)間:2019-01-17 09:34
【摘要】:研究了鋼鐵企業(yè)板坯庫天車調(diào)度問題,考慮了時(shí)間和空間以及熱軋計(jì)劃等實(shí)際限制,建立了一個(gè)板坯出庫天車調(diào)度模型.針對(duì)天車調(diào)度問題具有實(shí)時(shí)性和不可交叉性的特點(diǎn),設(shè)計(jì)了基于優(yōu)先關(guān)系的天車分配編碼方式、離散事件動(dòng)態(tài)仿真解碼、自適應(yīng)交叉算子以及在交叉和變異后進(jìn)行模擬退火局域搜索的Memetic算法.通過某鋼廠板坯出庫過程中天車調(diào)度的實(shí)際數(shù)據(jù)對(duì)模型和算法進(jìn)行仿真測試,實(shí)驗(yàn)結(jié)果表明:該算法具有很高的收斂性和穩(wěn)定性,滿足實(shí)際生產(chǎn)需要.
[Abstract]:In this paper, the scheduling problem of crane for slab storehouse in iron and steel enterprises is studied. Considering the practical constraints such as time and space and hot rolling plan, a scheduling model of crane for slab out of storage is established. Aiming at the real-time and non-intersecting characteristics of the crane scheduling problem, a priority relation based coding method is designed for the dynamic simulation and decoding of discrete events. Adaptive crossover operator and Memetic algorithm for simulated annealing local search after crossover and mutation. The model and algorithm are simulated and tested by the actual data of crane dispatching in a steel plant. The experimental results show that the algorithm has high convergence and stability and meets the actual production needs.
【作者單位】: 東北大學(xué)信息科學(xué)與工程學(xué)院;東北大學(xué)工商管理學(xué)院;東北大學(xué)秦皇島分校經(jīng)濟(jì)學(xué)院;
【基金】:國家自然科學(xué)基金資助項(xiàng)目(61573089,61333006,71601040) 河北省高等學(xué)校社科研究基金資助項(xiàng)目(SQ162004)
【分類號(hào)】:TF341.4;TP18
本文編號(hào):2409907
[Abstract]:In this paper, the scheduling problem of crane for slab storehouse in iron and steel enterprises is studied. Considering the practical constraints such as time and space and hot rolling plan, a scheduling model of crane for slab out of storage is established. Aiming at the real-time and non-intersecting characteristics of the crane scheduling problem, a priority relation based coding method is designed for the dynamic simulation and decoding of discrete events. Adaptive crossover operator and Memetic algorithm for simulated annealing local search after crossover and mutation. The model and algorithm are simulated and tested by the actual data of crane dispatching in a steel plant. The experimental results show that the algorithm has high convergence and stability and meets the actual production needs.
【作者單位】: 東北大學(xué)信息科學(xué)與工程學(xué)院;東北大學(xué)工商管理學(xué)院;東北大學(xué)秦皇島分校經(jīng)濟(jì)學(xué)院;
【基金】:國家自然科學(xué)基金資助項(xiàng)目(61573089,61333006,71601040) 河北省高等學(xué)校社科研究基金資助項(xiàng)目(SQ162004)
【分類號(hào)】:TF341.4;TP18
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