A decentralised multi-objective sustainable supply chain model under intuitionistic fuzzy environment

Kamal, Murshid; Gupta, Srikant; Ali, Irfan

doi:10.1504/ijmor.2020.106906

Cited by 13 publications

(6 citation statements)

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“…[26] In 2020, in a research conducted by Kamal et al, using different fuzzy sets and multiobjective fuzzy planning in multi-objective sustainable supply chain in order to increase Profit Maximization (PRMA) income and reduce cost and risk and choose the best supplier achieved. [27] Guderzian et al ( 2020) in their research using a multi-objective mixed-integer nonlinear programming model (MINLP) to increase efficiency and reliability in transporting pharmaceutical goods to customers. The planning model used in this research includes 3 opposing objective functions, for evaluation criteria to evaluate the quality of nondominated solutions of meta-heuristic algorithms (using 3 meta-heuristic algorithms).…”

Section: Literature Reviewmentioning

confidence: 99%

“…Equation (26) shows that the amount of product sent from the supplier to the Miandoab oil depot by pipeline should be between the upper and lower limits of the tank. Equation (27) shows that amount of product sent from the supplier to the Miandoab oil depot by the tanker must be between the upper and lower limits of the tank.…”

Section: Definition Of Objective Functions and Constraintsmentioning

confidence: 99%

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A Multi-Objective Optimization Model for Energy Allocation and Petroleum Products Distribution in Green Supply Chains (Case Study of IRAN National Petroleum Corporation MIANDOB)

Attaria,

Ejlaly,

Ghahvechia

2023

Preprint

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The oil industry plays an important role in global energy demand. Oil and other fossil fuels have been a major cause of environmental and global warming for decades. Many industries need oil as a major energy source, and it is important to minimize the environmental impact of oil( minimizing greenhouse gas (GHG)) and maximize its benefits Petroleum Revenue Management Act (PRMA). The environmental impact of the oil industry is the emission of gases such as carbon dioxide, sulfur dioxide, and nitrogen oxide, which directly and indirectly affect the environment.So it is important, creating a green supply chain network(GSCN) model that pursues several goals.This study presents a multi-objective optimization model for energy allocation and petroleum product distribution in green supply chains.For this purpose a multi-objective mixed-integer programming (MIP) model is formulated to develop. The proposed model is designed a green supply chain(GSC) to reduce oil company costs and greenhouse gas(GHG) emissions under uncertain demand. We solve the proposed model with GAMS and present a case study to IRAN National Petroleum Corporation(INPC) MIANDOAB demonstrate the applicability and exhibit efficacy of the proposed model.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Definition Of Objective Functions and Constraintsmentioning

confidence: 99%

A Multi-Objective Optimization Model for Energy Allocation and Petroleum Products Distribution in Green Supply Chains (Case Study of IRAN National Petroleum Corporation MIANDOB)

Attaria,

Ejlaly,

Ghahvechia

2023

Preprint

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“…Recently, bi-level, multi-level and intuitionistic fuzzy programmings have been formulated for selecting green and sustainable suppliers in a supply chain and production management (Gupta et al ., 2018, 2021; Charles et al. , 2019; Kamal et al. , 2020; Khan et al.…”

Section: Literature Reviewmentioning

confidence: 99%

Multi-criteria decision analysis for pharmaceutical supplier selection problem using fuzzy TOPSIS

Modibbo

Mai

Ahmed

et al. 2022

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PurposeSupplier selection in the supply chain network (SCN) has strategic importance and involves multiple factors. The multi-criteria nature of the problem coupled with environmental uncertainty requires several procedures and considerations. The issue of decision-making in selecting the best among various qualified suppliers remains the major challenge in the pharmaceutical industry. This study investigated the multi-criteria multi-supplier decision-making process and proposed a model for supplier selection problems based on mixed-integer linear programming.Design/methodology/approachThe concept of principal component analysis (PCA) was used to reduce data dimensionality, and the four best criteria have been considered and selected. The result is subjected to decision-makers’ (DMs’) reliability test using the concept of a triangular fuzzy number (TFN). The importance of each supplier to each measure is established using fuzzy technique for order preference by similarity to an ideal solution approach, and the suppliers have ranked accordingly.FindingsThis study proposes a mixed integer linear programming model for supplier selection in a pharmaceutical company. The effectiveness of the proposed model has been demonstrated using a numerical example. The solution shows the model's applicability in making a sound decision in pharmaceutical companies in the space of reality. The model proposed is simple. Readily commercial packages such as LINDO/LINGO and GAMS can solve the model.Research limitations/implicationsThis research contributed to the systematic manner of supplier selection considering DMs’ value judgement under a fuzzy environment and is limited to the case study area. However, interested researchers can apply the study in other related manufacturing industries. However, the criteria have to be revisited to suit that system and might require varying ratings based on the experts' opinions in that field.Practical implicationsThis work suggests more insights practically by considering a realistic and precise investigation based on a real-life case study of pharmaceutical companies with six primary criteria and twenty-four sub-criteria. The study outcome will assist organizations and managers in conducting the best decision objectively by selecting the best suppliers with their various standards and terms among many available contenders in the manufacturing industry.Originality/valueIn this paper, the authors attempted to identify the most critical attributes to be preserved by the top managers (DMs) while selecting suppliers in pharmaceutical companies. The study proposed an MILP model for supplier selection in the pharmaceutical company using fuzzy TOPSIS.

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“…Nakiboglu and Bulgurcu (2021) extended the TOPSIS technique in an uncertain environment using the intuitionistic fuzzy set for the selection of the best raw material supplier for a Turkish textile company. Kamal et al (2020) explore a sustainable supplier selection problem with ambiguity and eliminate it using intuitionistic fuzzy numbers. To compare optimum solutions, fuzzy goal programming with distinct membership functions is employed.…”

Section: Literature Reviewmentioning

confidence: 99%

Application of Time Series Analysis to Supplier Selection Problem: A Problem of Multi-Objective Decision Making

Gupta

Gupta²,

Kamal

2022

Preprint

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In today’s competitive environment, markets have made the purchasing function an ever more necessary action in supply chain management while in the same manner the survival of a business, for the most part, depends largely on its supplier’s. An effective and efficient supplier can give a competitive edge to a business. In general, the supplier selection is a multi-objective decision-making problem that involves several quantitative and qualitative factors that helps in minimizing the net ordering cost, minimizing the transportation cost, and minimizing the late deliveries. If we look at the different circumstances of life, we cannot predict anything in advanced. Therefore, we have taken the case of ambiguity in input parameters. Interval type-2 trapezoidal fuzzy numbers have been used to present the ambiguity in the input parameters, and crisp equivalent form has been obtained by taking the expected value. We also have used exponential smoothing forecasting analysis for getting the specific demand for the product to avoid the losses of shortages. Finally, we have used an efficient fuzzy goal programming approach for obtaining the compromise solution. A numerical example has been given to illustrate the concepts of the proposed methodology.

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A decentralised multi-objective sustainable supply chain model under intuitionistic fuzzy environment

Cited by 13 publications

References 0 publications

A Multi-Objective Optimization Model for Energy Allocation and Petroleum Products Distribution in Green Supply Chains (Case Study of IRAN National Petroleum Corporation MIANDOB)

A Multi-Objective Optimization Model for Energy Allocation and Petroleum Products Distribution in Green Supply Chains (Case Study of IRAN National Petroleum Corporation MIANDOB)

Multi-criteria decision analysis for pharmaceutical supplier selection problem using fuzzy TOPSIS

Application of Time Series Analysis to Supplier Selection Problem: A Problem of Multi-Objective Decision Making

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