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Numerical modelling using fuzzy multi-objective optimisation for environmental sustainability in green supply chain manufacturing
The urgency of taking action to reduce greenhouse gas emissions is increasing all the time. Due to the considerable contribution of emissions from storing and manufacturing to global warming, business leaders must devise a sustainable green supply chain. The suggested work will find out the quantity required for manufacturing and backordering to fulfil the optimisation of profits while minimising the ecological cost of industrial emissions and waste management. The inventory cost function includes the costs of initial setup, inventory, and shortfall. It has also taken into account several goals concerning the production system’s per-cycle waste and the overall penalty cost. Defects in the manufacturing process and shortages are also considered. Due to uncertainty in real life situations, we have taken into account the use of triangular fuzzy numbers to describe information connected with modelling decision factors. Different techniques of defuzzification are used to transform the fuzzy parameters into their discrete counterparts. The resulted multi-objective crisp problem is reduced to a single objective optimisation problem with the help of fuzzy technique by taking into account linear degrees of membership functions. The resulted model will help to decide the quantity of products for per production cycle to maintain sustainability (economic as well as environmental). The generated model is demonstrated by means of the numerical example and results are compared for various defuzzification techniques.
Numerical modelling using fuzzy multi-objective optimisation for environmental sustainability in green supply chain manufacturing
The urgency of taking action to reduce greenhouse gas emissions is increasing all the time. Due to the considerable contribution of emissions from storing and manufacturing to global warming, business leaders must devise a sustainable green supply chain. The suggested work will find out the quantity required for manufacturing and backordering to fulfil the optimisation of profits while minimising the ecological cost of industrial emissions and waste management. The inventory cost function includes the costs of initial setup, inventory, and shortfall. It has also taken into account several goals concerning the production system’s per-cycle waste and the overall penalty cost. Defects in the manufacturing process and shortages are also considered. Due to uncertainty in real life situations, we have taken into account the use of triangular fuzzy numbers to describe information connected with modelling decision factors. Different techniques of defuzzification are used to transform the fuzzy parameters into their discrete counterparts. The resulted multi-objective crisp problem is reduced to a single objective optimisation problem with the help of fuzzy technique by taking into account linear degrees of membership functions. The resulted model will help to decide the quantity of products for per production cycle to maintain sustainability (economic as well as environmental). The generated model is demonstrated by means of the numerical example and results are compared for various defuzzification techniques.
Numerical modelling using fuzzy multi-objective optimisation for environmental sustainability in green supply chain manufacturing
Int J Interact Des Manuf
Gulia, Pinki (author) / Kumar, Rakesh (author) / Kaur, Gursimran (author) / Suryawanshi, Shubhangi (author)
2025-03-01
16 pages
Article (Journal)
Electronic Resource
English
Industrialisation , Sustainability , Green supply chain , Fuzzy set theory , Multi-objective optimization Engineering , Engineering, general , Engineering Design , Mechanical Engineering , Computer-Aided Engineering (CAD, CAE) and Design , Electronics and Microelectronics, Instrumentation , Industrial Design
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