| 引用本文: | 黄敏,宋敏,周宁宁,王兴伟.随机环境下带有私人信息的单机能力分配策略[J].控制理论与应用,2014,31(4):444~450.[点击复制] |
| HUANG Min,SONG Min,ZHOU Ning-ning,WANG Xing-wei.Capacity allocation strategy of a single facility with private information in random environment[J].Control Theory and Technology,2014,31(4):444~450.[点击复制] |
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| 随机环境下带有私人信息的单机能力分配策略 |
| Capacity allocation strategy of a single facility with private information in random environment |
| 摘要点击 1961 全文点击 1235 投稿时间：2013-05-26 修订日期：2013-11-01 |
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| DOI编号 10.7641/CTA.2014.30529 |
| 2014,31(4):444-450 |
| 中文关键词 能力分配 随机加工时间 私人信息 次梯度 |
| 英文关键词 capacity allocation random processing time private information sub-gradient |
| 基金项目 国家杰出青年科学基金资助项目(71325002, 61225012); 国家自然科学基金资助项目(71071028, 70931001, 1021061); 高等学校博士学科点专项科研基金优先发展领域资助项目(20120042130003); 高等学校博士学科点专项科研基金资助项目(20110042110024); 中央高校基本科研业务费专项资金资助项目(N110204003, N120104001, N130604004); 流程工业综合自动化国家重点实验室基础科研业务费资助项目(2013ZCX11). |
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| 中文摘要 |
| 本文研究随机环境下考虑私人信息的单机能力分配问题. 该问题中各部门的单位产品收益、需求信息及加工设备各时段的能力为私人信息,且各时段中产品的加工时间为随机变量. 本文采用设备方与各部门协商的方法对问题进行求解, 首先利用随机规划理论将能力分配问题清晰化, 然后利用拉格朗日松弛和泰勒级数展开方法进行协商机制设计, 接着给出基于偏转次梯度方法的协商参数更新法则, 最后综合上述过程给出最终的问题求解算法. 数值算例验证了算法的有效性并分析了关键参数对能力分配结果的影响. |
| 英文摘要 |
| Capacity allocation of a single facility with private information in random environment, in which the earning per unit and the demand for each organization as well as the manufacturing capability of facility are private and the product processing time for each organization is random, is investigated. A negotiation-based method between the facility and organizations is proposed to solve the capacity allocation problem with the following solving process. First, the stochastic programming theory is applied to clarify the proposed capacity allocation problem, and then the negotiation mechanism design is performed via Lagrangian relaxation and Taylor series expansion. Further, a method based on the deflected sub-gradient method is derived to update negotiation parameters. The combination of the above steps constitutes the final solution algorithm. Numerical examples demonstrate the efficiency of the proposed algorithm and also analyze the effect of key parameters on capacity allocation results. |
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