Research on Rough Set and Multi-Objective Liner Programming Based Approach to Supplier Selection in Engineering Project

Purpose Globalization of markets and pace of technological change have caused the growing importance of paying attention to supplier selection problem. Therefore, this study aims to choose the best suppliers by providing a mathematical model for the supplier selection problem considering the green factors and stochastic parameters. This paper aims to propose a multi-objective model to identify optimal suppliers for a green supply chain network under uncertainty. Design/methodology/approach The objective of this model is to select suppliers considering total cost, total quality parts and total greenhouse gas emissions. Also, uncertainty is tackled by stochastic programming, and the multi-objective model is solved as a single-objective model by the LP-metric method. Findings Twelve numerical examples are provided, and a sensitivity analysis is conducted to demonstrate the effectiveness of the developed mathematical model. Results indicate that with increasing market numbers and final product numbers, the total objective function value and run time increase. In case that decision-makers are willing to deal with uncertainty with higher reliability, they should consider whole environmental conditions as input parameters. Therefore, when the number of scenarios increases, the total objective function value increases. Besides, the trade-off between cost function and other objective functions is studied. Also, the benefit of the stochastic programming approach is proved. To show the applicability of the proposed model, different modes are defined and compared with the proposed model, and the results demonstrate that the increasing use of recyclable parts and application of the recycling strategy yield more economic savings and less costs. Originality/value This paper aims to present a more comprehensive model based on real-world conditions for the supplier selection problem in green supply chain under uncertainty. In addition to economic issue, environmental issue is considered from different aspects such as selecting the environment-friendly suppliers, purchasing from them and taking the probability of defective finished products and goods from suppliers into account.

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Multi-objective supplier selection with the new hybrid COAW method

International Journal of Supply Chain and Operations Resilience ◽

10.1504/ijscor.2021.115552 ◽

2021 ◽

Vol 5 (1) ◽

pp. 60

Author(s):

Elham Shadkam

Keyword(s):

Supplier Selection ◽

Multi Objective

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Incorporating data quality into a multi-product procurement planning under risk

Journal of Business and Industrial Marketing ◽

10.1108/jbim-02-2020-0108 ◽

2021 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Fereshte Shabani-Naeeni ◽

R. Ghasemy Yaghin

Keyword(s):

Data Quality ◽

Optimization Model ◽

Industry 4.0 ◽

Supplier Selection ◽

Raw Material ◽

Measure Data ◽

Content Type ◽

Multi Objective ◽

Procurement Planning

Purpose In the data-driven era, the quality of the data exchanged between suppliers and buyer can enhance the buyer’s ability to appropriately cope with the risks and uncertainties associated with raw material purchasing. This paper aims to address the issue of supplier selection and purchasing planning considering the quality of data by benefiting from suppliers’ synergistic effects. Design/methodology/approach An approach is proposed to measure data visibility’s total value using a multi-stage algorithm. A multi-objective mathematical optimization model is then developed to determine the optimal integrated purchasing plan in a multi-product setting under risk. The model contemplates three essential objective functions, i.e. maximizing total data quality and quantity level, minimizing purchasing risks and minimizing total costs. Findings With emerging competitive areas, in the presence of industry 4.0, internet of things and big data, high data quality can improve the process of supply chain decision-making. This paper supports the managers for the procurement planning of modern organizations under risk and thus provides an in-depth understanding for the enterprises having the readiness for industry 4.0 transformation. Originality/value Various data quality attributes are comprehensively subjected to deeper analysis. An applicable procedure is proposed to determine the total value of data quality and quantity required for supplier selection. Besides, a novel multi-objective optimization model is developed to determine the purchasing plan under risk.

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Fuzzy Goal Programming With Interval Type-2 for Solving Multi-Objective Sustainable Supplier Selection Problems

Handbook of Research on Recent Perspectives on Management, International Trade, and Logistics - Advances in Logistics, Operations, and Management Science ◽

10.4018/978-1-7998-5886-7.ch010 ◽

2021 ◽

pp. 164-197

Author(s):

Nurullah UMARUSMAN

Keyword(s):

Supply Chain ◽

Goal Programming ◽

Supplier Selection ◽

De Novo ◽

Fuzzy Goal Programming ◽

Multi Objective ◽

Sustainable Supplier Selection ◽

Fuzzy Goal ◽

Interval Type

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.

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