A hybrid multi-agent negotiation protocol supporting supplier selection for multiple products with synergy effect

Supplier selection is an important problem in supply chain management. In practice, it is common for a purchasing company to procure a bundle of products simultaneously. In this regard, synergy effect could exist between products and hence affect the final choice of suppliers. It is therefore necessary to incorporate the synergy effect between products in supplier selection process. Agent-based negotiation models are applied to automate supplier selection process. Negotiation protocol is an essential component should be considered when building an effective agent negotiation model. The objective of this research is to propose a negotiation protocol special for multi-product supplier selection problem. The negotiation protocol is a hybrid multi-agent protocol of combinatorial procurement auction protocol and multi-bilateral bargaining protocol. The negotiation protocol is able to support the purchasing company and suppliers negotiate on the concrete commitments of multiple products simultaneously, and select suppliers for multiple products. In addition, both the purchasing company and suppliers can express their preferences on the synergy effect between products in negotiation process by adopting the negotiation protocol. Simulation is conducted to demonstrate the effectiveness and efficiency of the negotiation protocol.     

Model for negotiating the price and due date for a single order with multiple suppliers in a make-to-order environment

The nature of the business of a make-to-order company complicates its procurement activities. This paper is concerned with the development of a model for price and due-date negotiations between a manufacturer and its multiple suppliers in fulfilling a single order from a customer in a make-to-order environment. The developed negotiation model incorporates several established negotiation theories: aspiration level, limit level, natural forces acting on a negotiator and effective alternatives. Instead of presenting a single alternative for an offer in the current round of negotiation, we apply the Interactive Weighted-Tchebycheff method to generate a set of effective alternatives for presentation to the decision-maker in each round of the negotiation process. By giving a set of alternatives, we provide a degree of freedom to incorporate the decision-maker's preference in making offers and counter-offers during the negotiation process.     

A four-phase AHP–QFD approach for supplier assessment: a sustainability perspective

Recently, companies have become increasingly aware of the need to evaluate suppliers from a sustainability perspective. Introducing the triple bottom line (economic, social, and environmental performance) into supplier assessment and selection decisions embeds a new set of trade-offs, complicating the decision-making process. Although many tools have been developed to help purchasing managers make more effective decisions, decision support tools, and methodologies which integrate sustainability (triple bottom line) into supplier assessment and selection are still sparse in the literature. Moreover, most approaches have not taken into consideration the impact of business objectives and requirements of company stakeholders on the supplier evaluation criteria. To help advance this area of research and further integrate sustainability into the supplier selection modelling area, we develop an integrated analytical approach, combining Analytical Hierarchy Process (AHP) with Quality Function Deployment (QFD), to enable the ‘voice’ of company stakeholders in the process. Drawing on the sustainable purchasing strategy development process, our AHP–QFD approach comprises four hierarchical phases: linking customer requirements with the company's sustainability strategy, determining the sustainable purchasing competitive priority, developing sustainable supplier assessment criteria, and lastly assessing the suppliers. An illustrative example is provided to demonstrate the application of the proposed approach.     

Pre-selection of suppliers through an integrated fuzzy analytic hierarchy process and max-min methodology

There are a variety of analytical models for supplier selection ranging from simple weighted techniques to complex mathematical programming approaches. However, these models are specifically aimed at supporting a decision maker in a single phase, especially in the final selection phase and they have failed to consider the supplier selection process from a holistic point of view. Although the methodology presented in this paper primarily focused on the prequalification of potential suppliers, the outputs of the previous phases, namely problem definition and formulation of criteria, are used as inputs in this methodology. The methodology utilises a fuzzy analytic hierarchy process (AHP) method to determine the weights of the pre-selected decision criteria, a max-min approach to maximise and minimise the supplier performances against these weighted criteria, and a non-parametric statistical test to identify an effective supplier set. This information supports decision makers in making the final selection with effective alternative choices. Potential application of the proposed methodology is demonstrated in Audio Electronics in Turkey's electronics industry.     

Sustainable Supplier Selection Model in Supply Chains During the COVID-19 Pandemic

As global supply chains become more developed and complicated, supplier quality has become increasingly influential on the competitiveness of businesses during the Covid-19 pandemic. Consequently, supplier selection is an increasingly important process for any business around the globe. Choosing a supplier is a complex decision that can result in lower procurement costs and increased profits without increasing the cost or lowering the quality of the product. However, these decision-making problems can be complicated in cases with multiple potential suppliers. Vietnam's textile and garment industry, for example, has made rapid progress in recent years but is still facing great difficulties as the supply of raw materials and machinery depends heavily on foreign countries. Therefore, it is extremely important for textile and garment manufacturing companies in Vietnam to implement an effective supplier evaluation and selection process. While multicriteria decision-making models are frequently employed to assist with supplier evaluation and selection problems, few of these models consider the problem under the condition of a fuzzy decision-making environment. The aim of this paper is to create a hybrid MCDM model using the Fuzzy Analytical Hierarchy Process (FAHP) model and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to assist the supplier selection process in the garment industry in a fuzzy decision-making environment. In this study, the FAHP method is used to evaluate the performance and the weight of each criterion. TOPSIS is then used to rank all potential suppliers. The proposed model is then applied to a real-world case study to demonstrate both the process of calculation as well as its real-world applicability. The results from the case study provide empirical evidence that the model is feasible. The proposed approach can also be used in combination with other MCDM models to better support decision makers and can be modified to be applied in similar supplier selection processes for different industries.     

Procedure for supplier selection based on Cpm applied to super twisted nematic liquid crystal display processes

The loss-based process capability index C _pm , sometimes called the Taguchi index, has been proposed to the manufacturing industry as a method to measure process performance. The index C _pm takes into account the targeting degree of the process, which essentially measures process performance based on average process loss. Based on the C _pm index, a mathematically complicated approximation method was developed previously for selecting a subset of processes containing the best supplier from a given set of processes. The present paper implements this method and develops a practical step-by-step procedure to aid supplier selection decisions. The accuracy of the selection method is investigated using a simulation technique. The accuracy study provides useful information about the sample size required for a designated selection power. A two-phase selection procedure is developed to select a better supplier and to examine the magnitude of the difference between the two suppliers. Also investigated is a real-world case on the super twisted nematic liquid crystal display manufacturing process, and it is applied to the selection procedure using actual data collected from the factories to reach a decision in supplier selection.     

Supply chain network design with unreliable suppliers: a Lagrangian relaxation-based approach

This paper deals with the integrated facility location and supplier selection decisions for the design of supply chain network with reliable and unreliable suppliers. Two problems are addressed: (1) facility location/supplier selection; and (2) facility location/supplier reliability. We first consider the facility location and supplier selections problem where all the suppliers are reliable. The decisions concern the selection of suppliers, the location of distribution centres (DCs), the allocation of suppliers to DCs and the allocation of retailers to DCs. The objective is to minimise fixed DCs location costs, inventory and safety stock costs at the DCs and ordering costs and transportation costs across the network. The introduction of inventory costs and safety stock costs leads to a non-linear NP-hard optimisation problem. To solve this problem, a Lagrangian relaxation-based approach is developed. For the second problem, a two-period decision model is proposed in which selected suppliers are reliable in the first period and can fail in the second period. The corresponding facility location/supplier reliability problem is formulated as a non-linear stochastic programming problem. A Monte Carlo optimisation approach combining the sample average approximation scheme and the Lagrangian relaxation-based approach is proposed. Computational results are presented to evaluate the efficiency of the proposed approaches.     

A new method for workshop real time scheduling

Workshop real time scheduling is one of the key factors in improving manufacturing system efficiency. This is especially true for workshops in which various products are processed simultaneously, and use multipurpose machines. Real time scheduling is appropriate to handle perturbations in the environment of the manufacturing process, a major issue at the shop floor level. The products to be processed have release times and due dates and the resources are multipurpose machines. A decision support system for real time scheduling is described. It is based on an original approach, aiming at searching for characteristics of a set of schedules compatible with the main manufacturing constraints to be satisfied. This set of schedules is obtained by defining sequences of groups of permutable operations for every resource. A method to find such a set is described. We emphasize the use of this group sequence as a decision support system. Significant states and events requiring real time decisions are identified and three main types of decisions are analysed. For each of them, the proposed decision support system is detailed and explained.     

A fuzzy AHP evaluation model for buyer–supplier relationships with the consideration of benefits,opportunities, costs and risks

With increasingly fierce global competition, firms in various industries need to build a cooperative buyer–supplier relationship to survive and to acquire reasonable profit. Even though the literature on various types of collaboration between firms is abundant and the works on supplier selection models are numerous, the research that provides a mathematical model for the selection of the most appropriate form of buyer–supplier relationship is very limited. Existing buyer–supplier evaluation models usually only consider the benefits from the relationship, but not the opportunities, costs and risks that may need to be confronted. The main objective of this study is to propose an analytical approach to evaluate the forms of buyer–supplier relationship between a manufacturer and its supplier. A fuzzy analytic hierarchy process (AHP) model, which applies fuzzy set theory and the benefits, opportunities, costs and risks (BOCR) concept, is constructed to deal with uncertainty and to consider various aspects of alternatives. Multiple factors that affect the success of the relationship are analysed by incorporating experts’ opinions on their priority of importance, and a performance ranking of the buyer–supplier forms is obtained. A case study of selecting the most appropriate buyer–supplier form between a TFT-LCD manufacturer and its colour filter supplier is presented, and the proposed model is applied to facilitate the decision process. The proposed model is a general form that can be tailored and applied by firms that are making decisions on buyer–supplier relationship.     

基于FMEA的军队第三方物流供应商选择

目的 针对军队第三方物流供应商的选择问题,从风险视角对供应商完成军事保障任务过程中可能存在的风险进行识别和评估,以降低军事物流外包风险,为军队第三方物流供应商决策提供方法和思路。方法 提出可将FMEA技术运用于军队第三方供应商选择中的操作性框架,按照框架流程确定评价标准、识别潜在失效模式、决策分析,可更加全面、科学地对军队第三方供应商做出选择。结果 在不考虑风险的情况下,5家候选供应商中E的原始评分最高,D排名居中,但经过FMEA分析后,由于E在单项评价指标上的风险比例太大,而D的各项指标风险比原始排名靠前的供应商小很多,因此D成为军队最终选择的供应商。结论 利用FMEA分析军队第三方物流供应商选择问题,可以起到事先识别可能出现的失效模式,分析产生原因和可能导致的后果以及现有措施的可控程度,从而评估每位候选供应商在确定的评价标准中的风险大小,最后综合原始评分得出了供应商选择的结果。该方法操作简单、计算方便,能比较全面衡量军队第三方物流供应商的综合水平,有助于提高军队物资保障效率,降低物资保障风险。     

Fuzzy hybrid decision model for supplier evaluation and selection

This paper proposes a structured, integrated decision model for evaluating suppliers by combining the fuzzy analytical hierarchy process (FAHP) and grey relational analysis (GRA). The qualitative and partially-known information is incorporated in this decision model using the fuzzy set theory. In this proposed methodology, the weights of the evaluation criteria are calculated by using FAHP, then the ranking of the suppliers is determined by using GRA. Finally to show the robustness of the model, a sensitivity analysis is also performed. In this study, the supplier selection problem of an electroplating industry in the southern part of India was investigated, demonstrating the effectiveness of this developed integrated model. This model can help in solving the complex decision in supplier selection practice. The results generated from the model are properly validated and finally a systematic solution with decision support is provided for decision makers. This model can be integrated with other decision support systems of similar kinds of industries.     

Hesitant fuzzy programming technique for multidimensional analysis of hesitant fuzzy preferences

The linear programming technique for multidimensional analysis of preferences (LINMAP) is the most representative method for handling the multiple criteria decision making (MCDM) problems with respect to the preference information over alternatives. This paper utilizes the main structure of LINMAP to develop a novel hesitant fuzzy mathematical programming technique to handle MCDM problems within the decision environment of hesitant fuzzy elements (HFEs). Considering the hesitancy of the decision maker, both the pair-wise comparison preference information over alternatives and the evaluation information of alternatives with criteria are represented by the HFEs. Based on the incomplete pair-wise preference judgments over alternatives, we propose the concepts of the hesitant fuzzy consistency and inconsistency indices. Furthermore, we construct a hesitant fuzzy mathematical programming model to derive the weights of criteria and the positive-ideal solution. In this hesitant fuzzy programming model both the objective function and partial constraints’ coefficients take the form of HFEs, and an effective approach based on the ranking method of HFEs is further developed to solve the new derived model. To address the incomplete and inconsistent preference structures of criteria weights, we introduce several deviation variables and establish the bi-objective nonlinear programming model. At length, we employ a green supplier selection problem to illustrate the feasibility and applicability of the proposed technique and conduct a comparison analysis to validate its effectiveness.     

Mahalanobis Taguchi system based criteria selection tool for agriculture crops

Agriculture crop selection cannot be formulated from one criterion but from multiple criteria. A list of criteria for crop selection was identified through literature survey and agricultural experts. The identified criteria were grouped into seven main criteria namely, soil, water, season, input, support, facilities and threats. In this paper, Mahalanobis Taguchi system based tool was developed for identification of useful set of criteria which is a subset of the original criteria, for taking decision on crop selection in a given agriculture land. The combination of Mahalanobis distance and Taguchi method is used for identification of important criteria. Matlab software was used to develop the tool. After entering the values for each main criteria in the tool, it will process the value and identify the useful sub-criteria under each main criteria for selecting the suitable crop in a given agriculture land. Instead of considering all criteria, one can use these useful set of criteria under each main criteria for taking decision on crop selection in agriculture.     

Global supplier selection: a fuzzy-AHP approach

Global supplier selection has a critical effect on the competitiveness of the entire supply chain network. Research results indicate that the supplier selection process appears to be the most significant variable in deciding the success of the supply chain. It helps in achieving high quality products at lower cost with higher customer satisfaction. Apart from the common criteria such as cost and quality, this paper also discusses some of the important decision variables which can play a critical role in case of the international sourcing. The importance of the political-economic situation, geographical location, infrastructure, financial background, performance history, risk factors, etc., have also been pointed out in particularly in the case of global supplier selection. Supplier selection problem related to the global sourcing is more complex than the general domestic sourcing and as a result it needs more critical analysis, which could not be found properly in past available literatures. This paper discusses the fuzzy based Analytic Hierarchy Process (fuzzy-AHP) to efficiently tackle both quantitative and qualitative decision factors involved in selection of global supplier in current business scenario. The fuzzy-AHP is an efficient tool to tackle the fuzziness of the data involved in deciding the preferences of the different decision variables involved in the process of global supplier selection. The triangular fuzzy numbers are used to transform the linguistic comparison of the different decision criteria, sub-criteria and performance of the alternative suppliers. The pairwise comparison matrices help in deciding the synthetic extent value of each comparison and finally, the priority weights of one alternative over another are decided in this paper. An example from a manufacturing industry searching for the global supplier for a critical component is used to demonstrate the effective implementation procedure of proposed fuzzy-AHP technique. The proposed model can provide the guidelines and directions for the decision makers to effectively select their global suppliers in the current competitive business scenario.     

A distinct decision model for the evaluation and selection of a supplier for a chemical processing industry

The supplier selection process has gained importance recently due to the considerable amount of revenue spent on purchasing. The intention of this work is to develop an appropriate hybrid model by integrating the analytical hierarchy process (AHP) and grey relational analysis (GRA) for supplier evaluation and selection, which comprises three stages. In Stage I, the most influential criteria are selected by mutual-information-based feature selection. Stage II focuses on the determination of the weights of the attributes using AHP, while Stage III is used for the determination of the best supplier using GRA. The proposed model is illustrated using the case study of an electroplating industry to highlight the effectiveness and flexibility of the model. The model effectively combines specialised knowledge, experience and quantitative data to select the best suppliers. This paper presents the model development, solution and application processes of the proposed hybrid model for supplier selection. The decision support software was implemented in Excel to automate supplier selection. The proposed hybrid model is applied to enhance the decision-making process in supplier selection and also helps decision makers to effectively select suppliers.     

Contract negotiation and risk preferences in dual-channel supply chain coordination

This study employs profit-sharing contracts to coordinate dual-channel supply chains and examines the selection of profit-sharing parameters and the allocation of extra system profit gained from coordination. We characterise the Pareto-optimal contracts for the two- and three-stage dual-channel supply chains, by developing and maximising system utility function related to risk preferences and negotiating power. Under the optimal profit-sharing parameter in a two-stage supply chain, both members are reluctant to cooperate; however, in a three-stage supply chain, under the optimal two profit-sharing parameters selected by optimising the system utility function, the retailer is always reluctant to cooperate, but the distributor or the supplier may have incentives to deviate from cooperation. In this case, the distributor and the supplier will negotiate again as in a two-stage supply chain so that all three members can benefit from coordination with profit-sharing contracts. Besides acting independently, the distributor, in the process of contract negotiation, may choose to form an alliance with the upstream supplier or the downstream retailer, which means the relationship among the three members involving profit allocation after coordination is quite different from that for a two-stage supply chain and is not necessarily interest-contrary. In the contract negotiation, in any kind of scenario, risk aversion and negotiation power have a significant impact on the selection of optimal profit-sharing parameters and the allocation of extra system profit. One member’s risk aversion or its negotiation power may be advantageous to the other. Mathematical examples are illustrated to clarify the contract negotiation process.     

Selecting suppliers using a new fuzzy multiple criteria decision model: the fuzzy balancing and ranking method

In this paper, we present a fuzzy multiple criteria decision making (FMCDM) model known as fuzzy balancing and ranking. In contrast to other MCDM models, our proposed model does not require the weights of decision making criteria. First, we appraise the performance of alternatives against criteria via linguistic variables which are expressed as triangular fuzzy numbers. The foregoing model obtains the alternative rankings through a four-stage process. Second, an outranking matrix is derived indicating that the frequency with which one alternative is superior to all other alternatives based on each criterion. Third, the outranking matrix is triangularised to obtain an implicit pre-ordering or provisional order of alternatives. Fourth, the provisional order of alternatives is subjected to various screening and balancing operations that require sequential application of a balancing principle to the so-called advantages–disadvantages table that combines the criteria with the pair-wise comparisons of alternatives. Additionally, to demonstrate the procedural implementation of the proposed model and its effectiveness, we apply it on a case study regarding the problem of supplier selection.     

An integrated emergency ordering and production planning optimization model with demand and yield uncertainty

This paper proposes an integrated emergency ordering and production planning scheme for a multi-item, multi-product problem in which each product is composed of several ingredients. Each item can be supplied from both cheap unreliable suppliers prone to yield uncertainty and expensive reliable suppliers. A two-stage decision-making process is proposed in which orders are placed to the unreliable suppliers during the first stage and an emergency order can be placed in the second stage. In addition, a flexible backup ordering contract between the buyer and emergency supplier is proposed. A similar two-stage decision-making process is considered for production planning, where in the first stage, the main production plan is determined and in the second stage, the decision about a limited increase in the production plan is made as an emergency decision. An integrated ordering and production planning decision process is proposed for the problem. The value of emergency decisions, including the value of emergency ordering and the value of emergency production planning evaluates the effectiveness of the emergency decisions. Due to the staggering size of the problem, sample average approximation method is used to solve the problem.     

谈判能力不对称对供应商质量选择的影响分析

供应链成员的谈判能力不对称会影响供应商的质量改进投入.在谈判能力不对称情况下,建立一种供应商质量改进的决策模型,研究发现供应商的质量改进投入不能达到供应链最优水平.当供应商拥有较强谈判能力时,购买商对质量改进评价过程中存在的道德风险将降低供应商的质量改进投入;当购买商拥有较强谈判能力时,如果购买商提供给供应商长期的交易契约,质量改进投资风险率越大,供应商质量改进投入越低.经仿真比较,当供应商的初始质量较高时,供应商质量改进投入在购买商拥有较强谈判能力的情况下高于在供应商拥有较强谈判能力的情况.