A fuzzy model for supplier selection in quantity discount environments

Wang, Tai-Yue; Yang, Yih-Hwang

doi:10.1016/j.eswa.2009.03.018

Cited by 127 publications

(51 citation statements)

References 38 publications

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“…We then apply the fuzzy goal programming technique to obtain a compromised solution. The approach is based on the goal programming technique to solve the crisp goal programming problem given by [14]. The maximum value of any membership function can be 1; maximization of α ϵ [0,1].…”

Section: A Fuzzy Goal Programmingmethodsmentioning

confidence: 99%

“…Bevilacqua et al [13][5]* developed a fuzzy quality function deployment (QFD) approach for supplier selection problem. The quantitative techniques for supplier evaluation and selection can be categorized into three classes [14]: (1) multi-attribute decision making includes the linear weighting method and the analytical hierarchy process (AHP), (2) mathematical programming models include the linear programming models, mixed integer programming, multi-objective programming and data envelopment analysis, (3) intelligent approaches as for the last class include neural network based methods, expert systems, fuzzy decision making, hybrid approaches such as integrated AHP and linear programming, combined AHP, data envelopment analysis (DEA) and neural network has been applied for the supplier selection. Objective functions considered in the literature are minimizing the negative effect of vendor service rating, minimizing the negative effect of the economic environment [15], maximizing service and minimization of risk [16].…”

Section: Literature Reviewmentioning

confidence: 99%

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Incorporating carbon penalties into supplier selection in the supply chain

Gandhi¹,

Galar²,

Jha³

2014

Proceedings of Maintenance Performance Measurement and Management (MPMM) Conference 2014

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A navegação consulta e descarregamento dos títulos inseridos nas Bibliotecas Digitais UC Digitalis, UC Pombalina e UC Impactum, pressupõem a aceitação plena e sem reservas dos Termos e Condições de Uso destas Bibliotecas Digitais, disponíveis em https://digitalis.uc.pt/pt-pt/termos.Conforme exposto nos referidos Termos e Condições de Uso, o descarregamento de títulos de acesso restrito requer uma licença válida de autorização devendo o utilizador aceder ao(s) documento(s) a partir de um endereço de IP da instituição detentora da supramencionada licença.Ao utilizador é apenas permitido o descarregamento para uso pessoal, pelo que o emprego do(s) título(s) descarregado(s) para outro fim, designadamente comercial, carece de autorização do respetivo autor ou editor da obra.Na medida em que todas as obras da UC Digitalis se encontram protegidas pelo Código do Direito de Autor e Direitos Conexos e demais legislação aplicável, toda a cópia, parcial ou total, deste documento, nos casos em que é legalmente admitida, deverá conter ou fazer-se acompanhar por este aviso. Incorporating carbon penalties into supplier selection in the supply chain Autor(es):Gandhi, Kanika; Galar, Diego; Jha, P. C. Publicado por:Imprensa Abstract-Supply chain management (SCM) practices have flourished since the 1990s. Enterprises realize that a large amount of direct and indirect cost can be managed from effective and efficient SCM practices. Supplier selection has great impact on integration of the supply chain relationship. Effective and accurate supplier selection decisions are significant components for procurement and distribution management in many firms to enhance their organizational performance. In this study a multiple sourcing procurement distribution optimization problem is considered. Three objective functions are minimization of costs, maximization of performance and minimization of carbon emission penalty cost respectively. In order to solve the problem, a fuzzy mathematical model and a fuzzy goal programming solution approach are proposed to satisfy the decision maker's aspirations for fuzzy goals. A real life case study is given to illustrate how the model is utilized.

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Section: A Fuzzy Goal Programmingmethodsmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Incorporating carbon penalties into supplier selection in the supply chain

Gandhi¹,

Galar²,

Jha³

2014

Proceedings of Maintenance Performance Measurement and Management (MPMM) Conference 2014

View full text Add to dashboard Cite

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“…According to Wang and Yang (2009), the quantitative decision methods for solving the supplier selection problem can be classified into three categories: 1) multi-attribute decision-making, which includes the linear weighting method and the AHP, 2) mathematical programming models, which include the linear programming models, mixed integer programming, multi-objective programming and data envelopment analysis, and 3) intelligent approaches, which consist of neural network based methods, expert systems, fuzzy decision-making and hybrid approaches.…”

Section: Literature Reviewmentioning

confidence: 99%

An Integrated Mathematical Model for Supplier Selection

Asghari¹

2014

Industrial Engineering and Management Systems

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Extensive research has been conducted on supplier evaluation and selection as a strategic and crucial component of supply chain management in recent years. However, few articles in the previous literature have been dedicated to the use of fuzzy inference systems as an aid in decision-making. Therefore, this essay attempts to demonstrate the application of this method in evaluating suppliers, based on a comprehensive framework of qualitative and quantitative factors besides the effect of gradual coverage distance. The purpose of this study is to investigate the applicability of the numerous measures and metrics in a multi-objective optimization problem of the supply chain network design with the aim of managing the allocation of orders by coordinating the production lines to satisfy customers' demand. This work presents a dynamic non-linear programming model that examines the important aspects of the strategic planning of the manufacturing in supply chain. The effectiveness of the configured network is illustrated using a sample, following which an exact method is used to solve this multi-objective problem and confirm the validity of the model, and finally the results will be discussed and analyzed.

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“…To incorporate the imprecise aspiration levels of the goals, they formulated a vendor selection problem as a fuzzy mixed integer goal programming that includes three primary goals: minimizing the net cost, minimizing the net rejections, and minimizing the net late deliveries subject to realistic constraints regarding buyer's demand, vendor's capacity, vendor's quota flexibility, purchasing value of items, budget allocation to individual vendor, etc. Wang and Yang [16] searched supplier selection in a quantity discount environment using multi objective linear programming, AHP, and fuzzy compromise programming.…”

Section: Literature Reviewmentioning

confidence: 99%

The DEA Game Cross-efficiency Model for Supplier Selection Problem under Competition

Ma¹,

Yao²,

Jinand³

et al. 2014

Appl. Math. Inf. Sci.

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Abstract:As the most important responsibility of purchasing management, the problem of supplier evaluation and selection has always received a great deal of attention from practitioners and researchers. This management decision is a challenge due to the complexity and various criteria involved. Many methods based on data envelopment analysis(DEA) emerged, especially the cross efficiency. But it exists some limitations, such as the cross efficiency value is often non-unique, average cross efficiency measure is not good because it is not pareto solution. This paper considers the competition between the suppliers and presents game cross efficiency which is based on DEA to assess supplier performance. This method can get a unique efficiency and it is pareto solution. Numerical example is used to illustrate application and feasibility of the proposed methodology.

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A fuzzy model for supplier selection in quantity discount environments

Cited by 127 publications

References 38 publications

Incorporating carbon penalties into supplier selection in the supply chain

Incorporating carbon penalties into supplier selection in the supply chain

An Integrated Mathematical Model for Supplier Selection

The DEA Game Cross-efficiency Model for Supplier Selection Problem under Competition

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