A two-stage model for the design of supply chain networks

This research aims to develop an analytical model of the supplier selection process in designing a supply chain network. The constraints on the capacity of each potential supplier are considered in the process. The assumed objective of the supply chain is to minimize the level of customer dissatisfaction, which is evaluated by two performance criteria: (i) price and (ii) delivery lead time. The overall model operates at two levels of decision-making: the operational level and the chain level. The operational level concerns decisions related to optimizing the manufacturing and logistical activities of each potential supplier in order to meet the customer's requirements. At the chain level, all the bids from potential suppliers are evaluated and the final configuration of the supply chain is determined. The structure of the chain depends on the product specifications and on the customer's order size. An optimal solution in terms of the models for the two levels can be obtained by using a mixed-integer programming technique.     

A multi-objective robust optimization model for multi-product multi-site aggregate production planning in a supply chain under uncertainty

Manufacturers need to satisfy consumer demands in order to compete in the real world. This requires the efficient operation of a supply chain planning. In this research we consider a supply chain including multiple suppliers, multiple manufacturers and multiple customers, addressing a multi-site, multi-period, multi-product aggregate production planning (APP) problem under uncertainty. First a new robust multi-objective mixed integer nonlinear programming model is proposed to deal with APP considering two conflicting objectives simultaneously, as well as the uncertain nature of the supply chain. Cost parameters of the supply chain and demand fluctuations are subject to uncertainty. Then the problem transformed into a multi-objective linear one. The first objective function aims to minimize total losses of supply chain including production cost, hiring, firing and training cost, raw material and end product inventory holding cost, transportation and shortage cost. The second objective function considers customer satisfaction through minimizing sum of the maximum amount of shortages among the customers’ zones in all periods. Working levels, workers productivity, overtime, subcontracting, storage capacity and lead time are also considered. Finally, the proposed model is solved as a single-objective mixed integer programming model applying the LP-metrics method. The practicability of the proposed model is demonstrated through its application in solving an APP problem in an industrial case study. The results indicate that the proposed model can provide a promising approach to fulfill an efficient production planning in a supply chain.     

A decision method for supplier selection in multi-service outsourcing

Although supplier selection in multi-service outsourcing is a very important decision problem, research concerning this issue is still relatively scarce. This paper proposes a decision method for selecting a pool of suppliers for the provision of different service process/product elements. It pioneers the use of collaborative utility between partner firms for supplier selection. A multi-objective model is built to select desired suppliers. This model is proved to be NP-hard, so we develop a multi-objective algorithm based on Tabu search for solving it. We then use an example to show the applicability of the proposed model and algorithm. Extensive computational experiments are also conducted to further test the performance of the proposed algorithm.     

Applying fuzzy linguistic quantifier to select supply chain partners at different phases of product life cycle

Owing to rapidly growing global competition, enterprises are increasingly focusing on their core competencies. The focal company faces the challenge of creating alliances with more suppliers to create outsourcing synergy and provide heterogeneous products for customers. This study proposes a fuzzy multiple attribute decision making (FMADM) method based on the fuzzy linguistic quantifier. An attempt is made to ensure that the evaluation results satisfy the current product competition strategies, and also improve the effectiveness and efficiency of the entire supply chain. The fuzzy concept is applied to both the ordinal and cardinal information. Furthermore, the fuzzy linguistic quantifier guided order-weighted aggregation (FLQG-OWA) operator can be used to satisfy the enterprise product development strategy based on different phases of product life cycle.     

A strategic-tactical model for the supply chain design in the delocalization context: Mathematical formulation and a case study

In this paper, we propose a mathematical model for the design of supply chains in the delocalization context. Our main objective is to develop a strategic-tactical supply chain design model that integrates all the relevant components that characterize the delocalization problem. We adopt the activity based approach to model the problem and we focus on the logistic decisions of activity location, technology choice, supplier selection, etc., and the financial decisions of transfer pricing, transportation costs allocation, etc. The mathematical formulation is illustrated by a case study from the automotive sector. A comparison between the model solution and the real decisions is used to prove the applicability and the utility of the proposed model.     

基于改进TOPSIS法的供应商选择模型研究

为有效地帮助企业快速找到合适的供应商合作伙伴,采用直觉模糊集、评分函数等方法对TOPSIS评估法进行优化,并以此为基础建立了一种供应商选择模型。首先,采集和评估供应商的产品质量、产品价格、产品交货的可靠性、供应位置、财务情况、库存水平、劳资关系、发展能力和技术能力等相关信息,由专家给出主观评估信息,汇总为综合属性值;然后,通过直觉模糊熵确定各评估指标的权重;最后,综合考虑供应商选择决策过程中的多个目标和标准,应用改进TOPSIS法的对供应商进行分类选择。结果显示,基于改进TOPSIS法的供应商选择模型能够较准确地反映出各供应商的真实水平和对企业的潜在价值,可以有效地解决不确定条件下对供应商的选择问题,提高了供应商选择结果的可靠性。改进后的模型简便易行,具有良好的稳定性,对于合理制定企业供应商选择标准以及进一步优化决策模型具有一定的借鉴意义。     

The impact of supplier development on buyer competitive advantage: A path analytic model

As manufacturing firms increasingly realize that supplier performance is crucial to their establishing and maintaining competitive advantage, supplier development has been a subject of considerable research in supply chain management. We develop and test a path model to explore how supplier development practices affect buyer-supplier performance from the buying firm's perspective in the context of Hong Kong's electronics industry. The results show that top management, supplier evaluation, and supplier strategic objectives are significant determinants of transaction-specific supplier development, and that buyers that have closer collaborative relationships with suppliers may strengthen their competitive advantage.     

Dynamic supply chain modeling using a new fuzzy hybrid negotiation mechanism

The key part of dynamic supply chain management is negotiating with suppliers and with buyers. Coordination is essential for successful supply chain management. In order to model coordination among suppliers and buyers in a dynamic supply chain, this paper takes a step further and proposes a new fuzzy- logic-based hybrid negotiation mechanism. In most real-world negotiation situations, agents have a common interest to cooperate, but have conflicting interests over exactly how to cooperate. These situations involve restrictions and preferences that may be vaguely and partly defined. Therefore, this study takes the advantage of fuzzy logic and develops a hybrid negotiation-based mechanism, that combines both cooperative and competitive negotiations. Achieving effective coordination in a multi-agent system is non-trivial as no agent possesses the global view of the problem space. Moreover, the different strategies adopted by agents may produce conflicts. While agents coordinate with each other in the operations, they will negotiate about their strategies to reduce conflicts. The proposed fuzzy hybrid negotiation mechanism allows negotiation agents more flexibility and robustness in an automated negotiation system. The proposed mechanism not only helps sellers and buyers to explore various new choices and opportunities that the e-markets offer but also allows them to identify and analyze their resource constraints in a given schedule, and helps them to explore and exploit many alternatives for a better solution. The efficacy of the proposed approach is demonstrated through an illustrative example.     

A two-stage fuzzy-AHP model for risk assessment of implementing green initiatives in the fashion supply chain

Green or environmental concerns are drawing more and more attention both in academia and industry. Careful deployment of green initiatives or policies could not only fulfil the requirements of environmental legislation but also lead to a competitive advantage for firms. Nevertheless, making optimal decisions in this regard is not easy. This is principally due to two reasons: (1) the qualitative nature of, and (2) the uncertainty associated with, the parameters involved in the decision-making process. Analytic hierarchy process could be a useful tool to tackle the first challenge because of its ability to handle both qualitative and quantitative variables (decision criteria). Unfortunately, this approach is inadequate at addressing the uncertainties common in real-life applications. This challenge is particularly noticeable in the fashion industry since demand is very volatile, and there are many uncertain variables associated with the whole supply chain. As a result, this paper blends fuzzy logic, which is a popular method of incorporating uncertain parameters into the decision-making process, with analytic hierarchy process to form a selection (decision-making) model for different green initiatives in the fashion industry. The rationale behind the model is to analyse the associated risk of different alternatives, subject to different factors, be they deterministic or not. A numerical example is included in this paper to demonstrate how the proposed model works.     

A holistic network model for supply chain analysis

Supply chain researchers are experiencing a conceptual and analytical paradox. They are asked to move beyond dyadic analyses and investigate larger network effects with only a limited analytical toolkit. This research proposes the use of bilinear mixed-modeling to holistically analyze supply chain phenomena. Through this approach, researchers are able to account for multiple supply chain relationships, higher-order dependencies among member firms, and simultaneously evaluate covariates from buyer and seller perspectives. The model is validated through the lens of a pervasive supply chain problem commonly referred to as the bullwhip effect. A sample of firms from the US apparel industry in 2004 is analyzed and then the findings are confirmed using data from 2005. In addition to validating the model through the presence of the bullwhip effect, the bilinear model illuminates variables such as advertising, price deals, inventory turnover, and inventory backlogs that exacerbate or diminish inventory differences between firms in a supply chain. The results extend research on supply networks and supply efficiency to a more holistic level and show that higher-order dependencies are important drivers of supply chain phenomena.     

A co-ordination model combining incentive scheme and co-ordination policy for a single-vendor-multi-buyer supply chain

Incentive scheme and co-ordination policy are substantial components for the co-ordination of a decentralized supply chain system, but there is little work combining the two components as a single decision model (Li and Wang, 2007). This paper proposes a model which incorporates both incentive and co-ordination issues into a single co-ordination model for a single-vendor multi-buyer supply chain. In the proposed model, the co-ordination is achieved by synchronizing ordering and production cycles while price discount, which is based on the buyers’ order intervals, is used as the incentive to motivate buyers to participate in the co-ordination. While the vendor is benefited from the co-ordination by synchronized cycles, the proposed price discount scheme can guarantee that a buyer’s total relevant cost of co-ordination will be reduced when compared with independent optimization. More importantly, the proposed price discount scheme does not require any cost information from the buyers.     

A dynamic model for the optimization of decoupling point and production planning in a supply chain

In this paper, we propose a dynamic model to simultaneously determine the optimal position of the decoupling point and production-inventory plan in a supply chain such that the total cost of the deviation from the target production rate and the target inventory level is minimized. Using the optimal control theory, we derive the closed form of the optimal solution when the production smoothing policy and the zero-inventory policy are applied. The result indicates that under the production smoothing policy, the overestimation of demand rate during the pre-decoupling stage guarantees the existence of the optimal decoupling point; meanwhile the optimal decoupling point exists under zero-inventory policy when the demand rate is underestimated. Also we perform mathematical analysis on the behavior of the optimal production rate and the inventory level and the effect of problem parameters such as the length of the product life cycle and the forecast error on the performance.     

A tabu search heuristic for redesigning a multi-echelon supply chain network over a planning horizon

This paper addresses the problem of redesigning a supply chain network with multiple echelons and commodities. The problem belongs to a comprehensive class of network redesign problems previously introduced in the literature. Redesign decisions comprise the relocation of existing facilities to new sites under an available budget over a finite time horizon, the supply of commodities by upstream facilities, the inventory levels at storage facilities, and the flow of commodities through the network. The problem is modeled as a large-scale mixed-integer linear program. Feasible solutions are obtained by using a tabu search procedure that explores the space of the facility location variables. The latter prescribe the time periods in which changes in the network configuration occur. They are triggered by the setup of new facilities, which operate with capacity transferred from the existing facilities, and by closing the latter upon their entire relocation. As the problem is highly constrained, infeasible solutions with excess budget are allowed during the course of the search process. However, such solutions are penalized for their infeasibility. Computational experiments on realistically sized randomly generated instances indicate that this strategic oscillation scheme used in conjunction with tabu search performs very well.     

An improved algorithm and solution on an integrated production-inventory model in a three-layer supply chain

Ben-Daya et al. (2010) established a joint economic lot-sizing problem (JELP) for a three-layer supply chain with one supplier, one manufacturer, and multiple retailers, and then proposed a heuristic algorithm to obtain the integral values of four discrete variables in the JELP. In this paper, we first complement some shortcomings in Ben-Daya et al. (2010), and then propose a simpler improved alternative algorithm to obtain the four integral decision variables. The proposed algorithm provides not only less CPU time but also less total cost to operate than the algorithm by Ben-Daya et al. (2010). Furthermore, our proposed algorithm can solve certain problems, which cannot be solved by theirs. Finally, the solution obtained by the proposed algorithm is indeed a global optimal solution in each of all instances tested.     

基于消费者网络接受度的双渠道供应链补偿激励研究

线上直销渠道与线下零售渠道相结合构成的双渠道供应链是众多公司选择的销售模式,但也引发了线上渠道与线下传统零售渠道之间关于在商品定价、服务投入、信息共享之间的冲突。制造商通过对零售商提供一定的补偿能够有效协调双渠道供应链中存在于上述渠道中的冲突问题。针对这一问题,以消费者的网络接受程度变化为切入点,通过对双渠道供应链中制造商对零售商补偿激励与否的比较分析,得出结论:制造商实施补偿激励的方式能够有效协调渠道之间的冲突,激励零售商增加其销售努力程度,这种情况下存在着定价的最优解;同时,消费者的网络接受程度影响着最优定价策略、补偿激励水平、销售努力程度及供应链利润水平。此项研究为公司平衡线上直销与线下零售的双渠道销售模式提供了借鉴建议。     

Analogical reasoning for diagnosing strategic issues in dynamic and complex environments

Organizations interpret their environments by categorizing strategic issues as either opportunities or threats. They make such categorizations as inferences drawn from analogies from past experience. The accuracy of issue interpretations turns on: (1) which analogy is used, (2) what are the environment's properties, and (3) what is the timeframe? A computational model allows us to evaluate over time the accuracy of interpretations based on different forms of analogical reasoning in environments that differ in variation (unpredictability and dynamism) and complexity (dimensionality and ruggedness). This study elaborates a contingency approach to assessing analogical reasoning by organizations in which the form of analogical reasoning, environmental properties, and time all matter. Our findings indicate when particular forms of reasoning produce relatively more accurate inferences about opportunities and threats. Copyright © 2014 John Wiley & Sons, Ltd.     

Development of a process mining system for supporting knowledge discovery in a supply chain network

In today's competitive environment, business organizations are forced to maintain their competitive advantage by their ability to cut costs, increase revenue and uncover hidden issues. In order to enhance the visibility and transparency of value added information in a supply chain network, a process mining system is proposed for discovering a set of fuzzy association rules based on the daily captured logistics operation data, within the network. The proposed methodology provides all levels of employees with the ability to enhance their knowledge and understanding of the current business environment. Once interesting association rules have been extracted, organizations can identify the root-causes of quality problems in a supply chain and improve performance by fine-tuning the configuration of process parameters in specified processes. The application of the proposed methodology in a case company has also been studied. The prototype system has been developed and evaluated after performing a spatial analysis. The results obtained indicate that the system is capable of extracting high-quality and actionable information in the case company.     

Ordering and pricing policies in a manufacturing and distribution supply chain for fashion products

In the paper, we develop a model of manufacturing and distribution supply chains that are operating to meet price-sensitive random demand for products with short life cycles such as fashion products. Two specific scenarios are considered. The manufacturer-controlled scenario is one where the distributor shares price-sensitive random demand with the manufacturer, and the manufacturer controls the supply chain stocking decisions and bears the risk of overstocking costs. The distributor-controlled scenario works in the opposite direction. Prevailing wisdom suggests that the manufacturer should control supply chain decisions (e.g., via vendor-managed inventory). Our results indicate that such an arrangement is against the interest of a distributor selling short life-cycle products. Furthermore, we find that the total supply chain profit is generally higher when the distributor controls the supply chain stocking decisions and bears the risk of overstocking costs.