A fuzzy linear programming based approach for tactical supply chain planning in an uncertainty environment

This paper models supply chain (SC) uncertainties by fuzzy sets and develops a fuzzy linear programming model for tactical supply chain planning in a multi-echelon, multi-product, multi-level, multi-period supply chain network. In this approach, the demand, process and supply uncertainties are jointly considered. The aim is to centralize multi-node decisions simultaneously to achieve the best use of the available resources along the time horizon so that customer demands are met at a minimum cost. This proposal is tested by using data from a real automobile SC. The fuzzy model provides the decision maker (DM) with alternative decision plans with different degrees of satisfaction.     

Possibilistic linear-programming approach for supply chain networking decisions

Supply chain networking decisions are very important for the medium- and long-term planning success of manufacturing companies. The inputs to supply chain planning models are subject to environmental and system uncertainties. In this paper, a fuzzy set theory-based model is proposed to deal with those uncertainties. For this purpose, a possibilistic linear programming (PLP) model is used to make strategic resource-planning decisions using fuzzy demand forecasts and fuzzy yield rates as well as other inputs such as costs and capacities. The objective of the proposed PLP is to maximize the total profit of the enterprise. The model is applied to Mercedes–Benz Türk, one of the largest bus-manufacturing companies in the world, and conclusions and suggestions for further research are provided.     

A possibilistic decision model for new product supply chain design

This paper models supply chain (SC) uncertainties by fuzzy sets and develops a possibilistic SC configuration model for new products with unreliable or unavailable SC statistical data. The supply chain is modeled as a network of stages. Each stage may have one or more options characterized by the cost and lead-time required to fulfill required functions and may hold safety stock to prevent an inventory shortage. The objective is to determine the option and inventory policy for each stage to minimize the total SC cost and maximize the possibility of fulfilling the target service level. A fuzzy SC model is developed to evaluate the performance of the entire SC and a genetic algorithm approach is applied to determine near-optimal solutions. The results obtained show that the proposed approach allows decision makers to perform trade-off analysis among customer service levels, product cost, and inventory investment depending on their risk attitude. It also provides an alternative tool to evaluate and improve SC configuration decisions in an uncertain SC environment.     

不同风险态度下的三层供应链集成优化

研究了在决策者不同风险态度下的由供应商、分销商和零售商组成三层供应链集成优化问题。考虑供应链中价格、质量、交货、需求和供应的不确定风险因素为模糊变量,应用可信性理论建立了模糊机会约束规划模型,可信性测度的置信水平代表了决策者的风险偏好程度。使用模糊变量的乐观值和悲观值将机会约束转化为清晰的等价形式。最后,通过数值算例分析了决策者的风险态度的变化对集成供应链的影响。     

模糊连续需求下供应链收益共享契约机制研究

研究一个由供应商和零售商组成的两级供应链系统在模糊连续需求环境下的运作过程。将市场需求视为三角模糊数,利用模糊截集理论分析模糊连续需求下的分散决策和集中决策过程,并给出收益共享契约机制下的决策模型。研究结果表明：在模糊连续需求环境下,零售商的订购量存在唯一最优解;供应链系统的“双重边际化”效应同样存在;收益共享契约机制可以实现供应链中成员问的协调。最后,通过数值例子对模型进行了比较分析。     

Fuzzy goal programming for inventory management: A bacterial foraging approach

An efficient inventory planning approach in today’s global trading regime is necessary not only for increasing the profit margin, but also to maintain system flexibility for achieving higher customer satisfaction. Such an approach should hence be comprised of a prudent inventory policy and clear satisfaction of stakeholder’s goals. Relative significance given to various objectives in a supply chain network varies with product as well as time. In this paper, a model is proposed to fill this void for a single product inventory control of a supply chain consisting of three echelons. A generic modification proposed to the membership functions of the fuzzy goal-programming approach is used to mathematically map the aspiration levels of the decision maker. The bacterial foraging algorithm has been modified with enhancement of the algorithms’ capability to map integer solution spaces and utilised to solve resulting fuzzy multi-objective function. An illustrative example comprehensively covers various decision scenarios and highlights the underlying managerial insights.     

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.     

A dual-uncertainty-based chance-constrained model for municipal solid waste management

A double-sided dual-uncertainty-based chance-constrained programming (DDCCP) model was developed for supporting municipal solid waste management under uncertainty. The model was capable of tackling left-hand- and right-hand-side variables in constraints where those variables were affected by dual uncertainties (i.e. e.g. both fuzziness and randomness); and they were expressed as fuzzy random variables (FRVs). In this study, DDCCP model were formulated and solved based on stochastic and fuzzy chance-constrained programming techniques, leading to optimal solutions under different levels of constraints violation and satisfaction reliabilities. A long-term solid waste management problem was used to demonstrate the feasibility and applicability of DDCCP model. The obtained results indicated that DDCCP was effective in handling constraints with FRVs through satisfying them at a series of allowable levels, generating various solutions that facilitated evaluation of trade-offs between system economy and reliability. The proposed model could help decision makers establish cost-effective waste-flow allocation patterns under complex uncertainties, and gain in-depth insights into the municipal solid waste management system.     

不确定同时取送货车辆路径问题及粒子群算法研究

研究了不确定同时取送货车辆路径问题(VRPSPD),考虑运行环境的不确定性,顾客时间窗口要求和对顾客同时进行取货和送货服务的情况,以运作成本最低和顾客满意度最高为决策目标,构建不确定VRPSPD数学模型。模型中,引入模糊随机理论来描述决策环境中的双重不确定性,假定顾客需求量(送货量)和取货量是模糊随机变量。随后,提出基于模糊随机算子的改进粒子群算法对模型进行求解。为了适应模型特点和提高算法效率,设计合理的编码和解码过程,制定多个适应度函数方案处理多目标问题,并应用更加科学的更新策略。最后在应用案例中,通过参数测试获取合理的算法参数取值,采用计算结果分析和求解算法测评验证模型和算法的有效性。     

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.     

A multi-objective approach to supply chain visibility and risk

This paper investigates the twin effects of supply chain visibility (SCV) and supply chain risk (SCR) on supply chain performance. Operationally, SCV has been linked to the capability of sharing timely and accurate information on exogenous demand, quantity and location of inventory, transport related cost, and other logistics activities throughout an entire supply chain. Similarly, SCR can be viewed as the likelihood that an adverse event has occurred during a certain epoch within a supply chain and the associated consequences of that event which affects supply chain performance. Given the multi-faceted attributes of the decision making process which involves many stages, objectives, and stakeholders, it beckons research into this aspect of the supply chain to utilize a fuzzy multi-objective decision making approach to model SCV and SCR from an operational perspective. Hence, our model incorporates the objectives of SCV maximization, SCR minimization, and cost minimization under the constraints of budget, customer demand, production capacity, and supply availability. A numerical example is used to demonstrate the applicability of the model. Our results suggest that decision makers tend to mitigate SCR first then enhance SCV.     

供应链管理中加工/外包决策问题的模型

供应链管理中的一个核心问题是零部件的加工/外包决策。本在献[1]的两部门一种原材料，一种零部件的产量优化模型的基础上，提出了两部分和三部分多种原材料、多种零部件的产量优化模型，并在此基础上发展了企业的加工/外包决策模型。本的结果可为供应链管理中加工/外包决策问题提供科学的依据。     

A Fuzzy Principal Component Analysis Approach to Hierarchical Evaluation Model for Balanced Supply Chain Scorecard Grading

Effective performance management is critical to efficient supply chain management systems with the balanced scorecard as well as to effective evaluation models and their algorithms. Problems often encountered in the modeling of the balanced scorecard for supply chain are how to overcome the multicollinearity in its index system. In this paper, a new fuzzy hierarchical evaluation model featuring the criteria of the balanced supply chain scorecard is proposed and analyzed on the basis of data about Chinese firms. The model, based on the fuzzy weight’s matrix derived from a fuzzy principal component analysis, overcomes the multicollinearity in the index system of the balanced supply chain scorecard. This method proves good performance in determining the weight distribution matrix of the fuzzy hierarchical evaluation and improves the evaluation accuracy and generalization as shown for a group of firms in western China.     

A robust optimization approach to reduce the bullwhip effect of supply chains with vendor order placement lead time delays in an uncertain environment

Supply chain management is important for companies and organizations to improve their business and enhance competitiveness in the global marketplace. The bullwhip effect problem of supply chain systems with vendor order placement lead time delays in an uncertain environment is addressed in this paper. Among the numerous causes of bullwhip effect, we focus on uncertainties with respect to demand, production process, supply chain structure, inventory policy implementation and especially vendor order placement lead time delays. Minimizing the negative effect of these uncertainties in inducing bullwhip effect creates a need for developing dynamical inventory policy that increases responsiveness to demand and decreases volatility in inventory replenishment. First, a dynamic model of supply chain with above uncertainties is developed. Then, a novel uncertainty-dependent robust inventory control method using inventory position information is proposed. Additionally, the maximum allowable vendor order placement lead time delay that ensures the stability of supply chains and the suppression of bullwhip effect under the proposed inventory control policy is explored and measured. We find that vendor order placement lead time delays do play important role in supply chain dynamics and contribute to its turbulence and volatility. The effectiveness and flexibility of proposed method is verified through simulation study.     

Fuzzy control of a class of multivariable nonlinear systems subject to parameter uncertainties: model reference approach

This paper presents the fuzzy control of a class of multivariable nonlinear systems subject to parameter uncertainties. The nonlinear plant tackled in this paper is an nth-order nonlinear system with n inputs. If the input matrix B inside the fuzzy plant model is invertible, a fuzzy controller can be designed such that the states of the closed-loop system will follow those of a user-defined stable reference model despite the presence of parameter uncertainties. A numerical example will be given to show the design procedures and the merits of the proposed fuzzy controller.     

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。     

Inventory competition in a dual-channel supply chain with delivery lead time consideration

Aimed at the inventory competition of perishable products in a dual-channel supply chain with consideration of the delivery lead time in the online direct channel, we extend the Newsvendor model considering stock-out-based consumer switching behavior to include the delivery lead time. We examine the retailer's optimal order quantity decision in the retail channel and the manufacturer's optimal inventory level decision in the online direct channel, explore the manufacturer's optimal delivery lead time decision in the online direct channel, discuss the impact of the product price and consumer switching behavior on the optimal decisions of supply chain members, and compare the optimal decisions between decentralized and centralized scenarios. The results show that, compared with the centralized scenario, at least one of the supply chain members will overstock in the decentralized scenario and that consumers in the online direct channel enjoy a shorter delivery lead time and hence better service in the decentralized scenario. Finally, we present numerical examples to analyze the impact of relevant parameters on the supply chain members’ profits and the supply chain efficiency.     

A fuzzy newsvendor approach to supply chain coordination

In the absence of a clear command and control structure, a key challenge in supply chain management is the coordination and alignment of supply chain members who pursue divergent and often conflicting goals. The newsvendor model is typically used as a framework to quantify the cost of misalignment and to assess the impact of various coordination initiatives. The application of the newsvendor framework, however, requires the specification of some probability distribution for the sources of uncertainty, and in particular, for the market demand. The specification of an adequate demand distribution becomes difficult in the absence of statistical data. We therefore consider a fuzzy approach to the newsvendor problem. We use several fuzzy parameters in the model for the demand, the wholesale price, and the market sales price. We solve the fuzzy newsvendor problem to study three coordination policies: quantity discounts, profit sharing, and buyback. For each coordination policy, the optimal order quantity of the retailer is computed. The possible profits of the members in the supply chain are calculated with minimum sharing of private information. We further extend the fuzzy newsvendor model to a setting with a single manufacturer and multiple retailers under the assumption of ample capacity for the manufacturer. Detailed numerical examples are also provided.     

供应链融资模式下中小企业信用风险评估研究——基于左右得分的模糊TOPSIS算法

中小企业信用风险评价是供应链融资实现的关键。本文在对已进行的研究总结的基础上,建立了一套比较完整的评价指标体系,然后运用DEA、AHP和基于左右得分的模糊TOPSIS相结合的评价方法对中小企业在供应链融资中的信用风险进行评价。最后,将方法成功应用到具体实例,结果表明将AHP方法和左右得分模糊TOPSIS结合应用到多层次指标评价问题是合理、可行的,能够为供应链融资信用风险评估提供决策依据。     

基于货到付款支付模式且考虑银行存贷的二级供应链Stackelberg定价决策

在货到付款支付模式下二级供应链定价决策中,供应链企业资金闲置时向银行存款或资金约束时向银行贷款(银行存贷)的行为是不可忽视的重要因素,如何构建基于货到付款支付模式且考虑银行存贷的二级供应链Stackelberg定价决策模型是需要关注的重要问题。在本文中,首先给出了市场需求函数;然后,基于货到付款支付模式,针对制造商资金或零售商资金约束情形,分别构建针对不同供应链权力结构的定价决策模型;进一步地,通过模型求解确定了不同情形下不同权力结构的制造商与零售商的最优策略,并分析了模型参数对最优策略的影响;最后,针对不同资金约束情形与不同权力结构的最优策略以及银行利率对最优策略及利润影响,给出了对比分析。研究表明三种银行利率均会影响最优策略,且资金约束对象差异的影响明显。