基于模糊匹配的板坯入庫優化決策問題模型及求解

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基金項目:

國家自然科學基金資助項目(No.70771008

No.70371057)

中央高校基金科研業務費專項資金資助項目(No.FRF-AS-09-007B)

Model and algorithm for the slab location optimization decision problem based on fuzzy matching

1. School of Economics and Management, University of Science and Technology Beijing, Beijing 100083, China;
2. Engineering Research Center of MES Technology for Iron & Steel Production, Ministry of Education of China, Beijing 10083, China;
3. Project Department, Dongfang Boiler Group Co. Ltd., Zigong 643000, China

摘要: 針對板坯入庫優化決策問題,采用隸屬度函數表示待入庫板坯長度、寬度、厚度與各庫位已存板坯對應屬性的匹配程度,建立了板坯入庫模型.針對問題特征,借鑒遺傳算法的交叉和變異操作,設計了一種混合離散粒子群算法(DPSO-CM)進行求解.基于企業實際生產數據的仿真實驗驗證了模型和算法的可行性和有效性.
- 入庫優化 /
- 板坯入庫決策 /
- 模糊匹配 /
- 隸屬度 /
- 粒子群算法
Abstract: For solving the slab location decision problem with hybrid stowage, a slab location model using a membership function was built to express the level of matching on the related attributes of length, width and thickness between the storing slabs and stored slabs in a warehouse. According to the characteristics of the problem, a hybrid discrete particle swarm algorithm, called DPSO-MC, was proposed based on crossover and mutation in genetic algorithms. Experimental results on a real case of a steel plant demonstrate that the model and algorithm are feasible and effective.
- inventory optimization /
- slab location decision /
- fuzzy matching /
- membership function /
- particle swarm algorithm