控制理论与应用
控製理論與應用
공제이론여응용
CONTROL THEORY & APPLICATIONS
2009年
12期
1452-1454
,共3页
钢铁一体化生产%多目标优化%合同计划%NSGA-Ⅱ算法
鋼鐵一體化生產%多目標優化%閤同計劃%NSGA-Ⅱ算法
강철일체화생산%다목표우화%합동계화%NSGA-Ⅱ산법
integrated steel production%multi-objective optimization%order planning%NSGA-II algorithm
为了实现热装比最大等多个优化目标,将炼钢-连铸-热轧一体化生产过程,抽象为炼钢与热轧两大加工阶段,建立了一体化生产多目标合同计划模型.以板坯热装比最大、交货提前/拖期率最小和组炉余材最少为优化目标,综合考虑了炼钢产能、热轧产能、最小主体材产量、以及钢种、板坯和成品规格等约束条件.通过变异目标空间中的重合个体,以及在每一代增加若干个新个体的方法,对非支配排序遗传算法NSGA-Ⅱ (non-dominated sorting genetic algorithm)进行了改进,提高了种群的多样性.不同规模计划问题的计算结果表明了所建立模型和对NSGA-Ⅱ算法的改进是有效的.
為瞭實現熱裝比最大等多箇優化目標,將煉鋼-連鑄-熱軋一體化生產過程,抽象為煉鋼與熱軋兩大加工階段,建立瞭一體化生產多目標閤同計劃模型.以闆坯熱裝比最大、交貨提前/拖期率最小和組爐餘材最少為優化目標,綜閤攷慮瞭煉鋼產能、熱軋產能、最小主體材產量、以及鋼種、闆坯和成品規格等約束條件.通過變異目標空間中的重閤箇體,以及在每一代增加若榦箇新箇體的方法,對非支配排序遺傳算法NSGA-Ⅱ (non-dominated sorting genetic algorithm)進行瞭改進,提高瞭種群的多樣性.不同規模計劃問題的計算結果錶明瞭所建立模型和對NSGA-Ⅱ算法的改進是有效的.
위료실현열장비최대등다개우화목표,장련강-련주-열알일체화생산과정,추상위련강여열알량대가공계단,건립료일체화생산다목표합동계화모형.이판배열장비최대、교화제전/타기솔최소화조로여재최소위우화목표,종합고필료련강산능、열알산능、최소주체재산량、이급강충、판배화성품규격등약속조건.통과변이목표공간중적중합개체,이급재매일대증가약간개신개체적방법,대비지배배서유전산법NSGA-Ⅱ (non-dominated sorting genetic algorithm)진행료개진,제고료충군적다양성.불동규모계화문제적계산결과표명료소건립모형화대NSGA-Ⅱ산법적개진시유효적.
In order to realize the maximal hot charge-ratio and other optimal objectives, an optimal multi-objective order-planning model is formulated for the integrated steelmaking-continuous casting-hot rolling (SM-CC-HR) production process in a steel plant, where the steelmaking and the hot-rolling are regarded as the key steps. The objectives are the maximum of the hot charge-ratio, the minimum of the earliness/delayed delivery-time and the minimum of the slabs which are surplus to the requirements for hot rolling. The main constraints, including steelmaking and hot-rolling production capacities, the low limit of staple materials output, steel grade, slab and product dimension, are all taken into consideration in the model. The NSGA-Ⅱ algorithm (non-dominated sorting genetic algorithm) is improved by mutating the superposition individuals in the objective space and adding some new individuals on every generation so that the population diversity is improved significantly. Computation results of different order-planning problems indicate that the proposed mathematical model and the improvement on NSGA-Ⅱ algorithm are efficient.