模糊环境下动态供应商选择的混合整数非线性规划模型

基于供应商选择问题的动态性和模糊性,考虑在每个周期内生产商的需求能力及供应商的供应能力为模糊变量,本文将一个多阶段多商品多渠道的供应商选择问题视为一个0-1混合整数模糊动态非线性规划问题,目标函数为总成本最小化。然后建立了0-1混合整数模糊动态非线性规划模型。为了求解该模型,通过可信性理论把模型中模糊机会约束清晰化,将该模型转化为一个确定型的0-1混合整数动态非线性规划模型。最后给出了一个数值算例验证了模型的可行性。     

煤业集团供应商选择的可拓方法

结合煤业集团的实际，提出了供应商选择的指标体系。应用可拓学的理论与方法，结合熵理论，建立了基于熵权的可拓综合评价模型。由于在该模型中采用了熵权，从而避免了低层次多因素权重确定的主观性；该模型以综合关联度作为评价准则，避免了评价中的主观性。通过将该模型在平顶山煤业集团供应商选择中进行应用，得出了其最佳的供应商。而且评价过程表明，该方法易于操作和使用。     

基于ANP-RBF神经网络的化工行业绿色供应商选择

基于绿色供应链理念,提出了化工行业绿色供应商选择的特色指标,构建了化工行业绿色供应商选择的ANP-RBF神经网络模型。通过ANP确定各指标权重,再结合RBF神经网络,从训练数据中提取隐含的知识和规律,能够方便地用于新供应商的选择。该模型求解算法为增量算法,具有很好的可扩展性,从而增加了评价的动态性。算例验证结果表明,将ANP-RBF神经网络模型用于化工行业绿色供应商的选择具有较强的实用性。     

An a posteriori decision support methodology for solving the multi-criteria supplier selection problem

This research presents a novel, state-of-the-art methodology for solving a multi-criteria supplier selection problem considering risk and sustainability. It combines multi-objective optimization with the analytic network process to take into account sustainability requirements of a supplier portfolio configuration. To integrate ‘risk’ into the supplier selection problem, we develop a multi-objective optimization model based on the investment portfolio theory introduced by Markowitz. The proposed model is a non-standard portfolio selection problem with four objectives: (1) minimizing the purchasing costs, (2) selecting the supplier portfolio with the highest logistics service, (3) minimizing the supply risk, and (4) ordering as much as possible from those suppliers with outstanding sustainability performance. The optimization model, which has three linear and one quadratic objective function, is solved by an algorithm that analytically computes a set of efficient solutions and provides graphical decision support through a visualization of the complete and exactly-computed Pareto front (a posteriori approach). The possibility of computing all Pareto-optimal supplier portfolios is beneficial for decision makers as they can compare all optimal solutions at once, identify the trade-offs between the criteria, and study how the different objectives of supplier portfolio configuration may be balanced to finally choose the composition that satisfies the purchasing company's strategy best. The approach has been applied to a real-world supplier portfolio configuration case to demonstrate its applicability and to analyze how the consideration of sustainability requirements may affect the traditional supplier selection and purchasing goals in a real-life setting.     

Supplier selection and order allocation problem using a two-phase fuzzy multi-objective linear programming

The aim of this paper is to solve a supplier selection problem under multi-price level and multi-product using interactive two-phase fuzzy multi-objective linear programming (FMOLP) model. The proposed model attempts to simultaneously minimize total purchasing and ordering costs, a number of defective units, and late delivered units ordered from suppliers. The piecewise linear membership functions are applied to represent the decision maker’s fuzzy goals for the supplier selection and order allocation problem, and can be resulted in more flexibility via an interactive decision-making process. To demonstrate effectiveness of the proposed model, results of applying the proposed model are shown by a numerical example. The analytical results show that the proposed approach is effective in uncertain environments and provide a reliable decision tool for integrated multi-objective supplier selection problems.     

An integrated FCM and fuzzy soft set for supplier selection problem based on risk evaluation

Supplier selection problem, considered as a multi-criteria decision-making (MCDM) problem, is one of the most important issues for firms. Lots of literatures about it have been emitted since 1960s. However, research on supplier selection under operational risks is limited. What’s more, the criteria used by most of them are independent, which usually does not correspond with the real world. Although the analytic network process (ANP) has been proposed to deal with the problems above, several problems make the method impractical. This study first integrates the fuzzy cognitive map (FCM) and fuzzy soft set model for solving the supplier selection problem. This method not only considers the dependent and feedback effect among criteria, but also considers the uncertainties on decision making process. Finally, a case study of supplier selection considering risk factors is given to demonstrate the proposed method’s effectiveness.     

An integrated approach for supplier selection in multi-item/multi-supplier environment

One of the important stages in supply chain management which regards all the activities from the purchasing of raw material to final delivery of the product is the supplier selection process. Since it is the first stage of the supply chain management, it is a critical process affecting the consecutive stages. It is simply desired to select the best supplier for a specific product. But since there are a lot of criteria and alternatives to be considered, numerous decision making models have been proposed to provide a solution to this problem. Within this study, an integrated approach including fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and a mixed integer linear programming model is developed to select the best supplier in a multi-item/multi-supplier environment. The importance value of each supplier with respect to each product is obtained via fuzzy TOPSIS in the first stage. Then in the second stage, these values are used as an input in the mathematical model which determines the suppliers and the quantities of products to be provided from the related suppliers. So as to validate the proposed methodology, an application is performed in air filter sector.     

指派问题在供应商选优决策中的应用

通常供应链中供应商选优问题为多指标决策问题,本将此问题视为指派问题。指派问题中的关键是确定“效率”矩阵,本充分利用供应商单排序结果,评价指标权重以及供应商指标评价值构造了“效率”矩阵,建立了供应商综合选优指派问题模型,案例试算表明该方法合理、有效,为多指标方案决策提供了又一种可行的决策方法。     

基于产品平台的多目标供应商预选方法研究

由于供应商选择问题直接影响着企业的最终收益, 所以它对企业来说一直是一个重要的决策问题. 在以往的研究中, 供应商选择仅仅是从产品零部件的角度去考虑而没有从产品的整体出发. 此外, 传统的供应商选择都是发生在产品设计阶段之后的产品生产阶段. 然而, 在产品设计初期考虑供应商选择问题可以有效地避免合适供应商的短缺问题. 提出了一个基于产品平台的多目标供应商预选方法, 并在产品设计初期从产品整体角度建立了一个以最小化产品族外包成本、最小化产品族生产风险以及最小化供应商供应时间为多目标的优化模型, 从而有助于决策者在产品开发的早期对产品整体设计方案进行改善. 此外, 由于产品平台存在部件共享问题, 因此在优化模型中也考虑了部件共享对供应商预选结果的影响. 采用非支配排序遗传算法(NSGA-II)对优化模型进行求解, 并通过实际案例来说明提出的优化方法以及求解算法的合理性和有效性.     

A decision model for supplier selection in the presence of dual-role factors

Best suppliers help manufacturers to gain and sustain a competitive advantage by improving product quality, reducing cost, shortening lead-time and so on. The crucial role played by suppliers in a supply chain renders the selection of a supplier or suppliers a significant work that attracts the attention of both researchers and practitioners. In the literature, data envelopment analysis (DEA) as a nonparametric technique is often applied to conduct a performance analysis. Little attention, however, has been paid to dual-role factors in the supplier selection process. This paper proposes a novel two-step approach to select suppliers in the presence of dual-role factors. As a combination of DEA and two-person zero-sum game theory, our work considers the strategic behaviour of the external environment and is able to handle the supplier selection in a competitive environment. Moreover, the proposed model circumvents the requirement to specify the status of a dual-role factor ahead of an evaluation and is easy to solve. Finally, the applicability of the procedure is illustrated by an application to a data set of 18 suppliers.     

Restricting weights in supplier selection decisions in the presence of dual-role factors

One of the uses of data envelopment analysis (DEA) is supplier selection. Weight restrictions allow for the integration of managerial preferences in terms of relative importance levels of various inputs and outputs. As well, in some situations there is a strong argument for permitting certain factors to simultaneously play the role of both inputs and outputs. The objective of this paper is to propose a method for selecting the best suppliers in the presence of weight restrictions and dual-role factors. This paper depicts the supplier selection process through a DEA model, while allowing for the incorporation of decision maker’s preferences and considers multiple factors which simultaneously play both input and output roles. The proposed model does not demand exact weights from the decision maker. This paper presents a robust model to solve the multiple-criteria problem. A numerical example demonstrates the application of the proposed method.     

考虑供应链风险和绩效的供应商选择的模糊动态非线性多目标规划模型

基于供应链风险和供应链绩效的模糊性和供应商选择问题的动态性,本文考虑供应链风险和供应链绩效作为模糊变量,讨论如何给生产商一个满意的动态多目标供应商选择方案,确定供应链风险和总成本最小,以及供应链绩效最大。然后对该问题提出了一个动态多目标多产品供应商选择模型,该模型是首次同时考虑供应商选择,订单分配,供应链风险和供应链绩效的一个模糊动态非线性多目标规划模型。为了去模糊化和求解该模型,给出了一个风险和绩效的模糊评估法。最后给出一个数值算例验证了该模型的可行性,为决策者选择供应商提供了理论依据。     

Supplier selection using axiomatic fuzzy set and TOPSIS methodology in supply chain management

The current paper presents a comprehensive methodology for supplier selection. In the first stage, the linguistic values expressed as trapezoidal fuzzy numbers are used to assess the weights of the criteria. The Axiomatic Fuzzy Set clustering (AFS) method, which handles ambiguity and fuzziness in the supplier selection problem effectively, is applied to cluster the suppliers and evaluate each potential supplier that aims at obtaining initial supplier ranking. In the second stage, the Fuzzy Analytic Hierarchy Process (FAHP) model is constructed to determine the weight of various quantitative and qualitative criteria. To address multiple decision criteria in supplier ranking, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is employed to select the final suppliers. A numerical example composed of 30 suppliers and 6 criteria is studied, and the experimental results show that the proposed evaluation framework is suitable for supplier selection decisions even with the dependent criteria/attributes.     

Optimizing product assortment under customer-driven demand substitution

The problem of product assortment and inventory planning under customer-driven demand substitution is analyzed and a mathematical model for this problem is provided in this paper. Realistic issues in a retail context such as supplier selection, shelf space constraints, and poor quality procurement are also taken into account. The performance of three modified models, one that neglects customers’ substitution behavior, another that excludes supplier selection decision, and one that ignores shelf space limitations, are analyzed separately with computational experiments. The results of the analysis demonstrate that neglecting customer-driven substitution or excluding supplier selection or ignoring shelf space limitations may lead to significantly inefficient assortments. The effects of demand variability and substitution cost on optimal assortment and supplier selection decisions as well as on the optimal revenue are also investigated. The main contribution of this paper is the development of a practical and flexible model to aid retailers in finding optimal assortments to maximize the expected profit.     

基于粗糙集-层次分析法的制造业供应商评价选择

制造企业在确定供应商过程中,必须对供应商进行评价和选择,由于制造业的加工设备和加工工艺的复杂性,同时要确保供应商供货稳定和质量保证等多方面的因素,其评价指标体系必然有别于其它行业的评价指标.采用粗糙集属性约简的方法,对供应商评价选择指标进行约简分析,运用层次分析法对供应商进行评价选择.     

Controlling for supplier switching in the presence of real options and asymmetric information

Applying a real option approach, this paper examines how asymmetric information alters key variables of a firm’s supplier switching process, such as the timing of contracting (hurried versus delayed contracting), transfer payments, set-up, switching, and abandonment decisions. In a symmetric information setting, delayed contracting is unambiguously beneficial. Abandoning the once established relation with the entrant supplier is never an issue. In contrast, under asymmetric information hurried contracting with potentially abandoning the relation can be beneficial. Consistent with adverse selection models, we find that under delayed contracting, in equilibrium, the firm switches less frequently to the entrant supplier (switching inertia). Surprisingly, we also find that under hurried contracting the firm switches more frequently to the entrant supplier (switching acceleration) and may abandon the relation. Finally, we study how these key variables of the supplier switching process change when also the incumbent supplier has private information (two-sided asymmetric information case).     

Suppliers selection in the presence of both cardinal and ordinal data

Traditionally, supplier selection models are based on cardinal data with less emphasis on ordinal data. However, with the widespread use of manufacturing philosophies such as just-in-time (JIT), emphasis has shifted to the simultaneous consideration of cardinal and ordinal data in supplier selection process. To select the best suppliers in the presence of both cardinal and ordinal data, this paper proposes an innovative method, which is based on imprecise data envelopment analysis (IDEA). A numerical example demonstrates the application of the proposed method.     

Fuzzy multi-objective programming for supplier selection and risk modeling: A possibility approach

Selection of supply chain partners is an important decision involving multiple criteria and risk factors. This paper proposes a fuzzy multi-objective programming model to decide on supplier selection taking risk factors into consideration. We model a supply chain consisting of three levels and use simulated historical quantitative and qualitative data. We propose a possibility approach to solve the fuzzy multi-objective programming model. Possibility multi-objective programming models are obtained by applying possibility measures of fuzzy events into fuzzy multi-objective programming models. Results indicate when qualitative criteria are considered in supplier selection, the probability of a certain supplier being selected is affected.     

虚拟第三方下供应链激励协调

为了解决供应商隐藏成本信息、销售商隐藏努力行动所引起的逆向选择和道德风险问题,文章基于委托代理理论,引入虚拟第三方为协调主体,分别站在供应商和销售商的角度,通过设计合适的契约激励销售商努力工作和供应商“说真话”。研究结果表明,当供应链中只有道德风险存在时,可以通过如(16)式的契约(其中契约参数λ∈[0,1])实现供应链的完美协调;但是,当供应链中不仅仅存在道德风险还存在逆向选择时,该契约参数不再是区间[0,1]上任意的值,而是与供应链交易量q及供应商的生产成本c相关的定值(满足(29)式),此时的供应链才能实现协调;在该契约下,为获得更多的利益,供应商更有动机降低自身生产成本,销售商也更有积极性提高努力水平,从而实现“双赢”。最后,通过数值算例对模型进行了应用分析。     

Improving the efficiency of the purchasing process using total cost of ownership information: The case of heating electrodes at Cockerill Sambre S.A.

Improving the efficiency of the purchasing process provides important opportunities to increase a firm's profitability. In this paper we introduce a mathematical programming model that uses total cost of ownership information to simultaneously select suppliers and determine order quantities over a multi-period time horizon. The total cost of ownership quantifies all costs associated with the purchasing process and is based on the activities and cost drivers determined by an activity based costing system. Our approach is motivated by the purchasing problem of heating electrodes at Cockerill Sambre, a Belgian multinational steel producer. In this case quality issues account for more than 70% of the total cost of ownership making the quality of a supplier a critical success factor in the supplier selection process.