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A multi‐stage stochastic programming approach for network capacity expansion with multiple sources of capacity
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In networks, there are often more than one sources of capacity. The capacities can be permanently or temporarily owned by the decision maker. Depending on the nature of sources, we identify the permanent capacity, spot market capacity, and contract capacity. We use a scenario tree to model the uncertainty, and build a multi‐stage stochastic integer program that can incorporate multiple sources and multiple types of capacities in a general network. We propose two solution methodologies for the problem. Firstly, we design an asymptotically convergent approximation algorithm. Secondly, we design a cutting plane algorithm based on Benders decomposition to find tight bounds for the problem. The numerical experiments show superb performance of the proposed algorithms compared with commercial software. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 600–614, 2017 相似文献
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We study a component inventory planning problem in an assemble‐to‐order environment faced by many contract manufacturers in which both quick delivery and efficient management of component inventory are crucial for the manufacturers to achieve profitability in a highly competitive market. Extending a recent study in a similar problem setting by the same authors, we analyze an optimization model for determining the optimal component stocking decision for a contract manufacturer facing an uncertain future demand, where product price depends on the delivery times. In contrast to our earlier work, this paper considers the situation where the contract manufacturer needs to deliver the full order quantity in one single shipment. This delivery requirement is appropriate for many industries, such as the garment and toy industries, where the economies of scale in transportation is essential. We develop efficient solution procedures for solving this optimization problem. We use our model results to illustrate how the different model parameters affect the optimal solution. We also compare the results under this full‐shipment model with those from our earlier work that allows for multiple partial shipments. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007 相似文献
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When facing high levels of overstock inventories, firms often push their salesforce to work harder than usual to attract more demand, and one way to achieve that is to offer attractive incentives. However, most research on the optimal design of salesforce incentives ignores this dependency and assumes that operational decisions of production/inventory management are separable from design of salesforce incentives. We investigate this dependency in the problem of joint salesforce incentive design and inventory/production control. We develop a dynamic Principal‐Agent model with both Moral Hazard and Adverse Selection in which the principal is strategic and risk‐neutral but the agent is myopic and risk‐averse. We find the optimal joint incentive design and inventory control strategy, and demonstrate the impact of operational decisions on the design of a compensation package. The optimal strategy is characterized by a menu of inventory‐dependent salesforce compensation contracts. We show that the optimal compensation package depends highly on the operational decisions; when inventory levels are high, (a) the firm offers a more attractive contract and (b) the contract is effective in inducing the salesforce to work harder than usual. In contrast, when inventory levels are low, the firm can offer a less attractive compensation package, but still expect the salesforce to work hard enough. In addition, we show that although the inventory/production management and the design of salesforce compensation package are highly correlated, information acquisition through contract design allows the firm to implement traditional inventory control policies: a market‐based state‐dependent policy (with a constant base‐stock level when the inventory is low) that makes use of the extracted market condition from the agent is optimal. This work appears to be the first article on operations that addresses the important interplay between inventory/production control and salesforce compensation decisions in a dynamic setting. Our findings shed light on the effective integration of these two significant aspects for the successful operation of a firm. © 2014 Wiley Periodicals, Inc. Naval Research Logistics 61: 320–340, 2014 相似文献
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运用激励理论研究了军队工程招标采购过程中军方与承包商之间的关系,建立了军队工程招标激励模型。在不完全信息和竞争性招标中,投标人的行为是追求最大的效用,军方则需要建立一种机制诱使投标人按真实成本信息报价,以达到预期支付最小的目的。这种招标博弈的结果是军方与投标人之间达成贝叶斯纳什均衡(Bayesian Nash equilib- rium),即军方利用激励合同诱使投标人报出其真实成本,而投标人为达到中标目的则必须采取讲真话的占优策略,最终在双方均可接受的条件下达成协议。在此基础上,结合实际研究提出了改进的综合评标模型。 相似文献
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强制手段、利益诱导手段、劝告与指导手段是管理学中所倡导的主要管理手段。在我国利益诱导手段尚未引起重视。以“以人为本,构建社会主义和谐社会”为指导,分析讨论了利益诱导手段在公共消防安全管理中的应用,并详细分析了经济手段、保险手段、激励手段的具体内容,意在改变我国公共消防管理手段单一的局面。 相似文献
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在分析敏捷卫星的特点和卫星多用户需求的基础上,针对敏捷卫星任务规划问题,基于Multi-Agent理论构建了任务分配模型;针对敏捷卫星任务规划初始方案调度中卫星资源失效的情况给出了敏捷卫星动态任务重调度模型;在此基础上,提出了基于诚信机制的可解约合同网任务分配方法,设计了招投标机制、可解约合同网协议以及招投标、评标策略;以敏捷卫星任务规划调度问题为例通过实验获得了满意的结果,表明了模型的合理性以及算法的有效性。 相似文献