基于持续抽检的电力物资多阶段动态采购模型及系统

针对电力物资集中采购模式中由于采购批量大、合同周期长而导致的不稳定供应问题,提出一种多阶段迭代修正式的电力物资动态采购模型,运用持续质量抽检进行供应商动态调整。首先根据经济订购批量模型确定最佳招标批次、划分标包,并设定多阶段招标模式及供应商评价指标体系;同时依托供应商绩效评价系统,获取历史抽检数据并迭代预测各供应商物资质量,通过建立标包份额动态分配模型动态修正供应商供应量。通过具体案例对模型进行了示例和验证,并对产品质量与供货量的关联性进行了敏感性分析,为采购方有效控制物资质量、供应商提高中标率提供了指导。最后,介绍了项目组开发的一个基于移动物联网的电力物资送检系统,为本文所提的评价模型提供了可行的实施环境。     

组合预测分析方法及其在物资运输管理中的应用

在物流管理中运输问题非常重要,物资要实现实体转移,都需要通过运输来实现;而要达到运输费用的最小,必须使物资的需求具有前瞻性.根据现代经济学中的预测方法,结合企业物资历年实际需求情况,运用时间序列的趋势移动平均法、自适应滤波预测法、灰色预测法,利用层次分析法确定相应的权重后对未来物资需求进行组合预测,并应用于物资运输管理中,使运输费用达到最小,从而使运输管理更具有现实性及可操作性.     

关于物资采购招标中评标方法的探讨

结合货物采购招标案例,从评标方法、各项影响因素的权重、评标指标的确定等方面,对物资采购招标工作进行探讨,分析探讨招投标工作中的问题,提出招标工作中的相关建议,供在今后相关招标工作能够借鉴,从质量、技术、工艺、经验、服务等方面,达到提高物资采购招标水平的目地。     

多物品同时独立采购招标中的最优策略研究

主要研究了在多物品同时独立采购招标中投标商的最优投标策略。当有多个供应商同时对多个零部件报价时,指出了采购商应如何决定对各个供应商的最优分配量才能使采购成本最小。     

企业从物资采购管理方面提高经济效益

随着企业生产的不断扩大,企业越加关注企业物资采购管理,物资采购管理已成为现代企业生产经营管理的主要部分。本文从物资采购管理方面说明了提高企业经济效益的途径,如何控制成本,降低物资的进价,减少库存费用,使企业在物资采购管理方面达到利益最大化。     

逆向拍卖采购下的库存与定价联合决策

研究单周期下零售商的联合采购与定价决策问题。在该问题中,零售商首先确定一个采购合同,然后供应商投标,通过逆向拍卖选取一个获胜的供应商进行采购,同时确定产品的零售价格,目标是最大化其期望利润。假定需求函数是乘式的,在一定的条件下,证明零售商的期望收益(不包括采购费用)是采购量的凹函数,从而得到其最优的采购与定价策略。特别对正态需求分布情形给出了零售商的采购量和利润函数的解析表达式,并进行数值计算与分析。结果表明参与拍卖的供应商数量越多或供应商对其边际生产成本的估价越分散对零售商越有利。     

基于柔性契约的军队应急物资供应商选择

目的针对应急物资的供应商选择问题,希望通过与供应商之间签订柔性契约,以确保军队在应对突发灾害时能快速高效并且经济合理地获得救援物资。方法通过建立随机规划模型,可针对不同供应商提供的协议条款选择采购成本最少的供应商。结果运用该模型可分析得出,地处易发生Ⅰ,Ⅱ,Ⅲ,Ⅳ级灾害区域的军队采购部门在选择应急物资供应商时应重点协商的内容。结论军队采购部门与应急物资供应商之间签订柔性契约,能在保证物资供应的前提下尽可能降低总的采购成本,从而实现双方共赢。     

浅谈电力物资采购招标的两种模式

本文作者通过对物资采购招标模式的价值与意义进行了阐述,主要就电力物资采购招标的两种模式做了详细分析,同时就如何完善物资采购招标模式提出了相关的建议。希望为电力物资采购招标管理模式在物资管理工作与招标实践工作中提供一些有价值的信息,以供参考。     

供应链背景下煤矿物资采购经济管理对策解析

在供应链的大背景下,煤矿企业作为重要的组成部分,其物资采购成本和管理策略影响着企业的效益乃至整个供应链的正常有序运行,如何对物资采购进行有效管理,以实现降低采购成本和物资合理分配,提高企业物资采购效率,保障整个供应链系统的有效运作,从而提升企业的整体效益以及市场竞争力,本文将从煤矿物资的采购现状、管理方式等方面稍加探讨。     

浅谈机械行业物资采购中存在的问题及对策

随着科技的不断发展,社会生产力不断提高,各种各样的产品不断涌入市场,企业的物资采购工作面临许多新的问题。机械行业作为制造业中比重较大的行业,其物资采购成本一般占生产成本的40%—50%,采购成本的降低能为企业创造大量的利润。本文主要分析了机械行业采购的特点以及采购中面临的问题,如采购效率低、供应商管理不善、供应链不完善等,并根据问题提出了相应的对策及建议。     

第三方资金流提供商的采购协同问题研究

在传统的供应链采购运作过程中,由于核心制造商一直对其供应商供货采取下线结算的方式,从而导致供应商一直承担着巨大的库存持有成本.在基于Supply Hub的供应链运作模式下,提出了一种新的资金结算方式:令传统的3PL充当第三方资金流提供商来对供应商提前支付货款.从而解决供应商库存成本压力过大的问题,并且实现对资金流、信息流、物流的整合.在新的结算模式下,通过对供应链的成本分析研究得出一种有效的供应链运作机制,从而提高供应商的响应速度及协同性,降低供应链的总成本.通过数据模拟进一步证明.在该模式下核心制造商能够获得更快的产品交货期;供应商能够有效地降低库存持有成本;第三方资金流提供商可以通过对供应商采取适当的惩罚来约束供应商,促使供应商对交货期做出最合适的选择,并且使自身获利.     

The impact of contract parameters on the supply chain performance under different power constellations

Reporting forecast data is a common method used to improve the functioning of supply chains (SCs) and to reduce supply shortages. Customers tend to report the maximum possible demand as a forecast if restrictions are missing. Such a forecast is useless for suppliers. Hence, special contracts are needed to enhance the value of forecast data and therefore the cooperation between SC partners. In this paper, such a contract is presented. It encourages the customer to report a more realistic forecast. Deviations from the reported forecast are punished in different ways: If the customer reported too much and wants to release less than what was reported, he has to pay a penalty. On the other hand, the customer has the flexibility to purchase more than reported to meet the demand on his outlet but at the cost of an additional fee. This paper analyses how different contract parameters affect the performance of the SC, in particular when the bargaining power of customer and supplier is not equally distributed. Results show that the supplier and therefore the SC is better off if the supplier leaves the contractual cost parameters untouched but hides the true value of flexibility, especially when the customer is less powerful than the supplier.     

Revisiting rescheduling: MRP nervousness and the bullwhip effect

We study the material requirements planning (MRP) system nervousness problem from a dynamic, stochastic and economic perspective in a two-echelon supply chain under first-order auto-regressive demand. MRP nervousness is an effect where the future order forecasts, given to suppliers so that they may plan production and organise their affairs, exhibits extreme period-to-period variability. We develop a measure of nervousness that weights future forecast errors geometrically over time. Near-term forecast errors are weighted higher than distant forecast errors. Focusing on replenishment policies for high volume items, we investigate two methods of generating order call-offs and two methods of creating order forecasts. For order call-offs, we consider the traditional order-up-to (OUT) policy and the proportional OUT policy (POUT). For order forecasts, we study both minimum mean square error (MMSE) forecasts of the demand process and MMSE forecasts coupled with a procedure that accounts for the known future influence of the POUT policy. We show that when retailers use the POUT policy and account for its predictable future behaviour, they can reduce the bullwhip effect, supply chain inventory costs and the manufacturer’s MRP nervousness.     

客户化模式下面向产品的采购策略研究

分析了传统物料需求算法的不足和客户化模式下市场需求的特点,以采购BOM作为采购数据的组织形式和载体,采用语意数据模型化技术--IDEF方法,构建了采购BOM的生成过程模型,以实现采购数据与其他相关数据的集成管理.最后采取滚动计划的方法,并考虑安全库存和经济采购批量,给出了采购物料的生成算法模型,以实现库存的动态管理,提高采购的效益.     

An optimization model for phased supplier integration into e-procurement systems

Investment in e-procurement technologies has steadily increased in the past few years. Companies view these technologies as solutions to the problem of how to streamline the procurement process. Most companies find it necessary to integrate e-procurement technologies with their supply-base in a stepwise manner due to a large number of suppliers, varying levels of capabilities and the importance of suppliers, constrained resources, and the need to integrate various levels of e-procurement systems. However, research in e-procurement lacks a systematic tool to help firms to optimally integrate suppliers over a multiperiod horizon. This paper fills this gap by developing a multiperiod integer-programming model that assists managers to optimally integrate their supply base by considering a variety of factors that include integration costs, purchase amounts, purchase order frequencies, in addition to other constraints. We consider two scenarios that a firm can face: (i) the firm has all e-procurement technology levels in place before integrating with its suppliers; and (ii) the firm is still acquiring e-procurement technologies during the integration process with its suppliers. Results and sensitivity analyses from the two models are discussed and managerial implications are addressed.     

客户先期承诺:使供应链受益的一种有效方法

客户经常被价格上的折扣利益驱使而进行大批量订货采购或提前订货采购，一般情况下，这种低价格的刺激有利于供应链中的客户和供应商的成本降低。本文提出了通过获得客户先期订货承诺而使供应链获益的量化模型，并以原材料库存成本为例作了详细说明。     

Simultaneous planning of the project scheduling and material procurement problem under the presence of multiple suppliers

Simultaneous planning of project scheduling and material procurement can improve the project execution costs. Hence, the issue has been addressed here by a mixed-integer programming model. The proposed model facilitates the procurement decisions by accounting for a number of suppliers offering a distinctive discount formula from which to purchase the required materials. It is aimed at developing schedules with the best net present value regarding the obtained benefit and costs of the project execution. A genetic algorithm is applied to deal with the problem, in addition to a modified version equipped with a variable neighbourhood search. The underlying factors of the solution methods are calibrated by the Taguchi method to obtain robust solutions. The performance of the aforementioned methods is compared for different problem sizes, in which the utilized local search proved efficient. Finally, a sensitivity analysis is carried out to check the effect of inflation on the objective function value.     

模糊算法在库存控制中的应用

文章以某照明器材厂为实例，分析和讨论使用模糊控制技术在库存控制中的应用，通过模糊逻辑推理的方法，对该公司生产的整流器产品需求量进行预测，从而达到根据需求进行采购，实现最优的采购策略，达到降低库存费用的目的。在使用模糊逻辑进行推理预测的过程中，对于采用不同隶属函数进行推理的结果进行比较，从而确定了与实际较吻合的方案。     

A branch-and-bound algorithm for the concave cost supply problem

Effective supplier selection and allocation of order quantity among multiple suppliers are indispensable to the success of a manufacturing company. While companies have begun to turn into a comprehensive multi-criteria approach, most buyers still consider purchasing cost to be their primary concern in selecting their suppliers. In this paper, we consider the concave cost supply problem where a manufacturer seeks to select the suppliers and simultaneously procure the quantity of material/component required for production at the minimum total cost during a standard production period. We provide and validate an effective and efficient branch-and-bound algorithm that is finite and that finds the global optimal solution of the problem without any restrictions on the cost functions or on the set of input parameters used in the problem. Numerical experiments are conducted to evaluate the performance of the proposed algorithm.     

An integrated weighted fuzzy multi-objective model for supplier selection and order scheduling in a supply chain

This paper presents a new weighted fuzzy multi-objective model to integrated supplier selection, order quantity allocation and customer order scheduling problem to prepare a responsive and order-oriented supply chain in a make-to-order manufacturing system. Total cost and quality of purchased parts as well as the reliability of on-time delivery of customer orders are regarded as the objectives of the model. On the other hand, flexible suppliers can contribute to the responsiveness and flexibility of entire supply chain in the face of uncertain customer orders. Therefore, a mathematical measure is developed for evaluating the volume flexibility of suppliers and is considered as the other objective of the model. Furthermore, by considering the effect of interdependencies between the selection criteria and to handle inconsistent and uncertain judgments, a fuzzy analytic network process method is used to identify top suppliers and consider as the last objective. In order to optimise these objectives, the decision-maker needs to decide from which supplier to purchase parts needed to assemble the customer orders, how to allocate the demand for parts between the selected suppliers, and how to schedule the customer orders for assembled products over the planning time horizon. Numerical examples are presented and computational analysis is reported.