scholarly journals Multi-Objective Decision-Making In Supplier Selection: An Application Of Visual Interactive Goal Programming

2011 ◽  
Vol 15 (2) ◽  
pp. 57 ◽  
Author(s):  
Birsen Karpak ◽  
Rammahan R. Kasuganti ◽  
Erdogan Kumcu

<span>Supplier selection by purchasing teams in a supply chain management environment is inherently a multi-objective problem. The authors discuss one of the multiple criteria decision support systems; Visual Interactive Goal Programming (VIG), to assist purchasing teams in their vendor selection decisions. VIG is based on a multi-criteria technique known as Pareto Race. Two examples illustrate the application of VIG in different multi-objective supplier selection environments. The first example demonstrates the allocation of a single product among multiple vendors, while the second example focuses on a multiple-replenishment purchasing problem in selecting supplier and allocating orders among them. The authors conclude with a discussion of VIGs benefits and limitations.</span>

Author(s):  
Nurullah UMARUSMAN

Supply chain management is going on changing and developing in line with the needs of the growing global supply chain. Performance of supply chain, considered as a whole so that businesses can accommodate these evolvements and change, needs to be improved in the long run. Actually, businesses work with suppliers complying with their policies from past to present. However, other dimensions of sustainability should be considered, as well as economic criteria when selecting suppliers. With the right supplier selection made in this respect, by contributing to the efficient functioning of the supply chain, it will increase customer satisfaction, and therefore, the enterprises will reach the goals they set. The solution of the multi-objective sustainable supplier selection problem has been realized by using the “satisfied optimal supplier design” algorithm, also called fuzzy goal programming, with de novo-based interval type-2 proposed in this study.


Mathematics ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. 1621
Author(s):  
Irfan Ali ◽  
Armin Fügenschuh ◽  
Srikant Gupta ◽  
Umar Muhammad Modibbo

Vendor selection is an established problem in supply chain management. It is regarded as a strategic resource by manufacturers, which must be managed efficiently. Any inappropriate selection of the vendors may lead to severe issues in the supply chain network. Hence, the desire to develop a model that minimizes the combination of transportation, deliveries, and ordering costs under uncertainty situation. In this paper, a multi-objective vendor selection problem under fuzzy environment is solved using a fuzzy goal programming approach. The vendor selection problem was modeled as a multi-objective problem, including three primary objectives of minimizing the transportation cost; the late deliveries; and the net ordering cost subject to constraints related to aggregate demand; vendor capacity; budget allocation; purchasing value; vendors’ quota; and quantity rejected. The proposed model input parameters are considered to be LR fuzzy numbers. The effectiveness of the model is illustrated with simulated data using R statistical package based on a real-life case study which was analyzed using LINGO 16.0 optimization software. The decision on the vendor’s quota allocation and selection under different degree of vagueness in the information was provided. The proposed model can address realistic vendor selection problem in the fuzzy environment and can serve as a useful tool for multi-criteria decision-making in supply chain management.


2013 ◽  
Vol 3 (2) ◽  
pp. 1-8
Author(s):  
Monica Singhania ◽  
Gagan Gandhi

Subject area Supply chain management and particularly the significance of vendors as a strategic decision making tool. Study level/applicability The case is suitable for use in the following courses: MBA programs with specialisation in operations management where it can be used to teach students the significance of vendor selection and vendor rating in supply chain management (SCM); marketing research in management where it can be used to highlight the concept of multi attribute utility theory (MAUT) and its application; advanced statistics for multi criteria decision making (MCDM); and MBA/post graduate programs in management in strategic management where it can be used to introduce the concept of SWOT analysis and Porter's five forces model. An understanding of business process improvement will enable students get a comprehensive view about the case. Case overview This case showcases the concepts of MCDM and SCM in manufacturing industry. The company wanted to select vendors and rate them in each category of raw materials in order to have a competitive advantage over competitors. Since there are multiple attributes (often contradictory in nature) based on which the vendors would be selected Kaul, Vice-President, Commercial uses multi-attribute utility theory (MAUT) to help solve the problem. The case has implications for manufacturing industry in selecting vendors to meet a raw materials need. Expected learning outcomes The case can be used to understand management concepts such as market research, supply chain management and multi criteria decision making. It can be used to: teach complexities involved in identifying attributes for vendor selection and vendor rating; help understand supply chain management in business process improvement; help students understand the application of MCDM; and help MBA students studying marketing research. The case will also be useful to students in understanding the application of MCDM in operations management. Some knowledge about cigarette manufacturing will help students to realize the depth of the case. Supplementary materials Teaching notes are available for educators only. Please contact your library to gain login details or email [email protected] to request teaching notes.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Alireza Fallahpour ◽  
Morteza Yazdani ◽  
Ahmed Mohammed ◽  
Kuan Yew Wong

PurposeIn the last decade, sustainable sourcing decision has gained tremendous attention due to the increasing governmental restrictions and public attentiveness. This decision involves diverse sets of classical and environmental parameters, which are originated from a complex, ambiguous and inconsistent decision-making environment. Arguably, supply chain management is fronting the next industrial revolution, which is named industry 4.0, due to the fast advance of digitalization. Considering the latter's rapid growth, current supplier selection models are, or it will, inefficient to assign the level of priority of each supplier among a set of suppliers, and therefore, more advanced models merging “recipes” of sustainability and industry 4.0 ingenuities are required. Yet, no research work found towards a digitalized, along with sustainability's target, sourcing.Design/methodology/approachA new framework for green and digitalized sourcing is developed. Thereafter, a hybrid decision-making approach is developed that utilizes (1) fuzzy preference programming (FPP) to decide the importance of one supplier attribute over another and (2) multi-objective optimization on the basis of ratio analysis (MOORA) to prioritize suppliers based on fuzzy performance rating. The proposed approach is implemented in consultation with the procurement department of a food processing company willing to develop a greener supply chain in the era of industry 4.0.FindingsThe proposed approach is capable to recognize the most important evaluation criteria, explain the ambiguity of experts' expressions and having better discrimination power to assess suppliers on operational efficiency and environmental and digitalization criteria, and henceforth enhances the quality of the sourcing process. Sensitivity analysis is performed to help managers for model approval. Moreover, this work presents the first attempt towards green and digitalized supplier selection. It paves the way towards further development in the modelling and optimization of sourcing in the era of industry 4.0.Originality/valueCompetitive supply chain management needs efficient purchasing and production activities since they represent its core, and this arises the necessity for a strategic adaptation and alignment with the requirement of industry 4.0. The latter implies alterations in the avenue firms operate and shape their activities and processes. In the context of supplier selection, this would involve the way supplier assessed and selected. This work is originally initiated based on a joint collaboration with a food company. A hybrid decision-making approach is proposed to evaluate and select suppliers considering operational efficiency, environmental criteria and digitalization initiatives towards digitalized and green supplier selection (DG-SS). To this end, supply chain management in the era of sustainability and digitalization are discussed.


2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Qinghua Pang ◽  
Tiantian Yang ◽  
Mingzhen Li ◽  
Yi Shen

Due to the increasing awareness of global warming and environmental protection, many practitioners and researchers have paid much attention to the low-carbon supply chain management in recent years. Green supplier selection is one of the most critical activities in the low-carbon supply chain management, so it is important to establish the comprehensive criteria and develop a method for green supplier selection in low-carbon supply chain. The paper proposes a fuzz-grey multicriteria decision making approach to deal with these problems. First, the paper establishes 4 main criteria and 22 subcriteria for green supplier selection. Then, a method integrating fuzzy set theory and grey relational analysis is proposed. It uses the membership function of normal distribution to compare each supplier and uses grey relation analysis to calculate the weight of each criterion and improves fuzzy comprehensive evaluation. The proposed method can make the localization of individual green supplier more objectively and more accurately in the same trade. Finally, a case study in the steel industry is presented to demonstrate the effectiveness of the proposed approach.


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