An integrated multiobjective decision making process for supplier selection and order allocation

Supplier selection is a multi-criteria problem which includes both tangible and intangible factors. In these problems if suppliers have capacity or other different constraints two problems will exist: which suppliers are the best and how much should be purchased from each selected supplier? In this paper an integrated approach of analytic network process (ANP) and multi-objective mixed integer linear programming (MOMILP) is proposed to consider both tangible and intangible factors in choosing the best suppliers and define the optimum quantities among selected suppliers to maximize the total value of purchasing and minimize the budget and defect rate. The priorities are calculated for each supplier by using ANP. Four different plastic molding firms working with a refrigerator plant are evaluated according to 14 criteria that are involved in the four clusters: benefits, opportunities, costs and risks (BOCR). Also the priorities of suppliers will be used as the parameters of the first objective function. This multi-objective real-life problem was solved by using ε$\epsilon$-constraint method and a reservation level driven Tchebycheff procedure. Finally, the most preferred nondominated solutions were determined by considering decision maker's (DM) preferences and the results obtained by these techniques are compared.     

An integrated multi-objective decision-making process for multi-period lot-sizing with supplier selection

Supplier selection is a multi-criteria problem which includes both tangible and intangible factors. In these problems if suppliers have capacity or other different constraints two problems will exist: which suppliers are the best and how much should be purchased from each selected supplier? In this paper an integrated approach of analytic network process (ANP) and multi-objective mixed integer linear programming (MOMILP) is proposed. This integrated approach considers both tangible and intangible factors in choosing the best suppliers and defines the optimum quantities among selected suppliers to maximize the total value of purchasing (TVP), and to minimize the total cost and total defect rate and to balance the total cost among periods. The priorities are calculated for each supplier by using ANP. Four different plastic molding firms working with a refrigerator plant are evaluated according to 14 criteria that are involved in the four clusters: benefits, opportunities, costs and risks (BOCR). The priorities of suppliers will also be used as the parameters of the first objective function. This multi-objective and multi-period real-life problem is solved by using previous techniques and a reservation level driven Tchebycheff procedure (RLTP). Finally the most preferred nondominated solutions are determined by considering the decision maker's (DM's) preferences and the results obtained by these techniques are compared.     

The supplier selection problem with quantity discounts and truckload shipping

To minimize procurement expenditures both purchasing and transportation costs need to be considered. We study a procurement setting in which a company needs to purchase a number of products from a set of suppliers to satisfy customer demand. The suppliers offer total quantity discounts and transportation costs are based on truckload shipping rates. The goal is to select a set of suppliers so as to satisfy product demand at minimal total costs. The resulting optimization problem is strongly NP-hard. We develop integer programming based heuristics to solve the problem. Extensive computational experiments demonstrate the efficacy of the proposed heuristics and provide insight into the impact of instance characteristics on effective procurement strategies.     

An integrated supplier selection and inventory problem with multi-sourcing and lateral transshipments

In this research, we consider the supplier selection problem of a firm offering a single product via multiple warehouses. The warehouses face stationary, stochastic demand and replenish their inventory via multiple suppliers, to be determined from a set of candidates, with varying price, capacity, quality, and disruption characteristics. Additionally, the warehouses may simultaneously replenish their inventory from other warehouses proactively. With these characteristics, the problem is a multi-sourcing, supplier selection, and inventory problem with lateral transshipments. Even though the benefits of multi-sourcing and lateral transshipments have been presented in the literature individually to mitigate risks associated with uncertain demand and disrupted supply, the intertwined sourcing and inventory decisions under these settings have not been investigated from a quantitative perspective. We develop a decomposition based heuristic algorithm, powered with simulation. While the decomposition based heuristic determines a solution with supplier selection and inventory decisions, the simulation model evaluates the objective function value corresponding to each generated solution. Experimental results show, contrary to the existing literature, inferior decisions may result when considering the selection of suppliers solely on unit and/or contractual costs. We also evaluate the impact of multi-sourcing with rare but long disruptions compared to frequent but short ones.     

An analysis of the supplier selection process

Customers select suppliers based on the relative importance of different attributes such as quality, price, flexibility, and delivery performance. This study examines the difference between managers' rating of the perceived importance of different supplier attributes and their actual choice of suppliers in an experimental setting. We use two methods: a Likert scale set of questions, to determine the importance of supplier attributes; and a discrete choice analysis (DCA) experiment, to examine the choice of suppliers. The results indicate that although managers say that quality is the most important attribute for a supplier, they actually choose suppliers based largely on cost and delivery performance.     

Joint supplier selection and scheduling of customer orders under disruption risks: Single vs. dual sourcing

This paper presents a stochastic mixed integer programming approach to integrated supplier selection and customer order scheduling in the presence of supply chain disruption risks, for a single or dual sourcing strategy. The suppliers are assumed to be located in two different geographical regions: in the producer's region (domestic suppliers) and outside the producer's region (foreign suppliers). The supplies are subject to independent random local disruptions that are uniquely associated with a particular supplier and to random semi-global (regional) disruptions that may result in disruption of all suppliers in the same geographical region simultaneously. The domestic suppliers are relatively reliable but more expensive, while the foreign suppliers offer competitive prices, however material flows from these suppliers are more exposed to unexpected disruptions. Given a set of customer orders for products, the decision maker needs to decide which single supplier or which two different suppliers, one from each region, to select for purchasing parts required to complete the customer orders and how to schedule the orders over the planning horizon, to mitigate the impact of disruption risks. The problem objective is either to minimize total cost or to maximize customer service level. The obtained combinatorial stochastic optimization problem will be formulated as a mixed integer program with conditional value-at-risk as a risk measure. The risk-neutral and risk-averse solutions that optimize, respectively average and worst-case performance of a supply chain are compared for a single and dual sourcing strategy and for the two different objective functions. Numerical examples and computational results are presented and some managerial insights on the choice between the two sourcing strategies are reported.     

Analytical network process for software selection in product development: A case study

Application of software for manufacturing processes is one of the resolutions many enterprises have resorted to in the 21st century. This has been a result of increased complexity of products, globalization, rapid changes in technology and so on. The idea was that application of software especially for product development would increase the competitive advantage of industry nevertheless the irony has been that most of the investment in software has not achieved the expected results. We carry out a case study to introduce a methodology, the analytical network process as a multiattribute strategic decision making approach to help in the selection of appropriate software to suit the product development process of a particular product.     

Integration of the information systems in the production process: a case study

This paper evaluates the execution of an ERP – enterprise resource planning in a production process. The changes that were made to processes to make them compatible with ERP modules and adaptations that were required by the ERP implementation are presented. The presented study is different from the normal patterns of a vertical implementation, since its application is not direct. In order to use the standard modules of the ERP system, the internal processes were embellished and the data collection steps were integrated into the production process (production orders, inventory, production, daily consumption, daily output). The case study shows that the ERP implementation caused an improvement of the processes in the areas adjacent to production (purchasing, logistics, distribution, supply and sales). In conclusion, this paper presents the main advantages and disadvantages of the ERP system implementation, as well as some considerations and recommendations for the future ERP implementations.     

Global supplier development considering risk factors using fuzzy extended AHP-based approach

Global supplier development is a multi-criterion decision problem which includes both qualitative and quantitative factors. The global supplier selection problem is more complex than domestic one and it needs more critical analysis. The aim of this paper is to identify and discuss some of the important and critical decision criteria including risk factors for the development of an efficient system for global supplier selection. Fuzzy extended analytic hierarchy process (FEAHP) based methodology will be discussed to tackle the different decision criteria like cost, quality, service performance and supplier's profile including the risk factors involved in the selection of global supplier in the current business scenario. FEAHP is an efficient tool to handle the fuzziness of the data involved in deciding the preferences of different decision variables. The linguistic level of comparisons produced by the customers and experts for each comparison are tapped in the form triangular fuzzy numbers to construct fuzzy pair-wise comparison matrices. The implementation of the system is demonstrated by a problem having four stages of hierarchy which contains different criteria and attributes at wider perspective. The proposed model can provide not only a framework for the organization to select the global supplier but also has the capability to deploy the organization's strategy to its supplier.     

Impact of competitive conditions on supplier evaluation: a construction supply chain case study

This research proposes a multi-criteria decision-making (MCDM) framework and demonstrates the impact of competitive conditions on supplier evaluation process for construction supply chains. The paper focuses on the supply chain of a large-scale housing project in order to illustrate the role of competitive capability and suppliers’ profile and its influence on supplier evaluation based on prevailing supply/market conditions. Various scenarios are investigated to demonstrate the impact of competition on supplier evaluation. The contribution of the study lies in highlighting the impact of supply/market conditions on MCDM decisions causing supplier evaluation ‘imbalance’ and MCDM usage. It is expected that the study will be useful for project management, construction, supply chain management, sourcing professionals. The findings of the study are generalisable to projects-based situations such as petroleum refinery and ship building where bill of materials typically consists of thousands of items and a large number of suppliers are involved.     

Strategic goals and design drivers of the supplier portal: lessons from the Ferrari case

The purpose of this work is to identify the main design drivers of a supplier portal and to verify the relationships between these drivers and the strategic goals of such portals. Through the analysis of an empirical case, three different design drivers have been identified, called penetration, breadth, and depth. Moreover, a relationship has been found out between strategic goals and the identified design drivers. This relationship, based on the evidences of a currently successful field experience, can provide a framework to support the design of a supplier portal.     

Developing a supplier selection system through integrating fuzzy AHP and fuzzy DEA: a case study on an auto lighting system company in Taiwan

Supplier selection plays a very important role in supply chain management. This study intends to develop a novel performance evaluation method, which integrates both fuzzy analytical hierarchy process (AHP) method and fuzzy data envelopment analysis (DEA) for assisting organisations to make the supplier selection decision. Fuzzy AHP method is first applied to find the indicators’ weights through expert questionnaire survey. Then, these weights are integrated with fuzzy DEA. We use α -cut set and extension principle of fuzzy set theory to simplify the fuzzy DEA as a pair of traditional DEA model. Finally, fuzzy ranking using maximising and minimising set method is able to rank the evaluation samples. A case study on an internationally well-known auto lighting OEM company shows that the proposed method is very suitable for practical applications.     

The effect of supplier development on outsourcing performance: the mediating roles of opportunism and flexibility

Abstract

In this increasingly competitive business environment, firms utilise outsourcing as a strategic tool to leverage globally dispersed resources so that they may focus on their core competencies and improve efficiency. The more firms rely on outsourcing, the more they depend on their suppliers, and the more important it is to manage and develop suppliers in order to achieve and maximise the benefits of outsourcing. This paper explores the impact of supplier development on outsourcing performance. Structural equation modelling was used to analyse data collected from 213 manufacturing firms in China. The results indicate that supplier development has a strong direct positive impact on outsourcing performance, and that supplier development also leads to enhanced outsourcing performance through reducing outsourcing opportunism risk and improving outsourcing flexibility. In addition to making a contribution to current theories of outsourcing, our findings also provide outsourcing managers with practical understanding and insights about the role of supplier development in enhancing outsourcing performance.     

基于系统柔性的MTS-MTO混合生产决策

研究生产商采用MTS、MTO混合作业的方式为不同客户提供产品和服务的策略。计划利用一组可灵活控制的动态设备处理那些不同需求的MTS和MTO生产业务,为此,我们开发了一个多服务台的排队模型,利用拟生灭过程和相位型分布得到了MTS、MTO排队系统平衡条件和稳态概率矩阵几何解。通过求解分块矩阵方程组,给出了系统队列长度、平均等待队长、顾客服务水平等绩效测度指标。建立了系统运作成本最优化的数学模型,采用搜索算法,确定了关键参数的边界值,找到了混合系统运作的最优策略。数值模拟和系统绩效比较分析结果显示：（1）动态切换策略能够更快速的帮助MTS恢复目标库存量,控制系统缺货风险,降低库存持有成本;（2）找到了满足顾客服务水平的最少的设备配置数量和库存成本最低的生产切换时间,且动态系统的平均队列长度低于静态系统;（3）混合运作策略减少了约2/3的静态系统平均队列长度,企业在队列长度减小的窗口期内可以接受更多订单和缩短MTO订单交货时间。     

Procurement process: Decision by exclusion and pairwise comparisons

Two case studies illustrate multicriteria decision making techniques frequently used in procurement practice: least-cost sufficient performance and weighted utility optimization. Both techniques have defects and are rarely robust. Decision by exclusion and pairwise comparisons is proposed as a third approach which eliminates inferior alternatives by generalized forms of minimum performance requirements established under multicriteria framework. It is more robust and maintains high level of accountability.     

Unsanctioned practice innovation: A process model

This paper focuses on unsanctioned practice innovations (UPIs) and how they are generated and realized by those outside the senior ranks of an organisation. Through a longitudinal in-depth qualitative study of a multinational firm between 2001 and 2014, we discovered how deviance from formal procedural frameworks had diverse and often creative and productive effects that countered the constraints of transparency, legitimacy and top-down planning of practice innovations. Deviants enact a range of manoeuvres, often resulting in delegitimising prescribed practices and novel solutions to problems that an organisation encounters. We provide an analytical account of these UPIs, the manoeuvres necessary in their claims to legitimacy and the implications for more formal practice innovations.     

A model for integrated production-packaging systems

The problem of determining the economic packaging frequency of jointly replenished items has received a lot of attention from researchers. This problem is usually encountered while packaging the products after completing manufacture. Nevertheless, production batch quantities certainly influence the manufacturing cycle time of products and hence the economic packaging quantities for jointly replenished items. Therefore, realizing the importance of the relationship between production batch quantities and packaging quantities     

A novel portfolio selection model in a hybrid uncertain environment

The future returns of each securities cannot be correctly reflected by the securities data in the past, therefore the statistical techniques and the experts’ judgement and experience are combined together to estimate the security returns in the future. In this paper, the returns of each securities are assumed to be fuzzy random variables, then following the ideas of mean variance model a new portfolio selection model in a hybrid uncertain environment is proposed. Moreover, the λ-mean variance efficient frontiers and λ-mean variance efficient portfolios are defined, and the properties of λ-mean variance efficient portfolios located on different λ-mean variance efficient frontiers are discussed. Finally, a numerical example is presented to illustrate the proposed portfolio selection model. On the basis of the results, we can conclude that the proposed model can provide the more flexible results.     

延迟决策对一类产出系统演化的影响研究

企业作为有限理性的经济主体,在做下阶段的生产决策时可能不仅考虑本期而是要综合考虑以往连续多期的边际利润情况。研究表明,加入时滞以后,系统纳什平衡点的稳定域明显扩大,从而为在混沌经济系统中实现倍周期分岔控制提供了现实途径,同时,还会使系统在纳什平衡点出现hopf分岔等新的动力学演化行为。而且,以累积利润为指标的系统表现可以得到改善。首先引入延迟决策的企业将获得更大的相对竞争优势。而在两家企业都引入延迟决策的情况下,伴随第二家企业产量调整速度的增加,它们将交替获得竞争优势。     

Handling uncertain decisions in whole process design

In recent years, the chemical and pharmaceutical industries have observed a noticeable decline in economic activity. This has resulted in many companies focusing on innovative research and development as they consider this key to business success. In particular, a number of leading industrial organisations have adopted the principles of Whole Process Design (WPD). WPD considers the optimisation of the entire product development process, from raw materials to end product, rather than focusing on each individual unit operation. The complexity involved with the implementation of WPD requires rationalised decision-making, often with limited or uncertain information. This paper presents the outcomes of two questionnaires that examined the requirements of professionals working within the chemistry-using industries with respect to developing a decision-making support tool. From the findings a methodology is proposed, the outcome of which allows a decision-maker to visually interpret their decision results with associated levels of uncertainty. A chemical route selection case study demonstrates and validates the application of the proposed methodology.