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A Novel Integrated q-Rung Fuzzy Framework for Biomass Location Selection with No Apriori Weight Choices

Author

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  • Raghunathan Krishankumar

    (Department of Computer Science and Engineering, Amrita School of Computing, Amrita Vishwa Vidyapeetham, Coimbatore 641105, India)

  • Arunodaya Raj Mishra

    (Department of Mathematics, Government College Raigaon, Satna 485441, India)

  • Pratibha Rani

    (Department of Engineering Mathematics, Koneru Lakshmaiah Education Foundation, Vaddeswaram 522302, India)

  • Fausto Cavallaro

    (Department of Economics, University of Molise, Via De Sanctis, 86100 Campobasso, Italy)

  • Kattur Soundarapandian Ravichandran

    (Department of Mathematics, Amrita School of Physical Sciences, Amrita Vishwa Vidyapeetham, Coimbatore 641105, India)

Abstract

Biomass is a promising form of clean energy that could be utilized worldwide for huge household demand. As the world is constantly fighting climate change and carbon emissions, the adoption of biofuels for households minimizes the ill effects on the ecosystem from households. A recent report from IndiaSpend shows that Indian households bring approximately 3.78 tonnes/capita of carbon, which includes electricity, consumables, and food sources. To bring a balance between utilization demand and ecofriendliness within the household, biomass is an attractive option. Location for producing biomass is a crucial decision problem as it involves multiple criteria that are competing and conflicting with one another. Previous studies on location selection for biomass cannot promptly model uncertainty and consider hesitation and interactions of experts and criteria. To handle these issues, a novel integrated decision approach is put forward. Initially, a generalized orthopedic structure is adapted to model uncertainty from three dimensions. Further, the weights of experts and criteria are determined via variance measure and the CRITIC method. A ranking procedure is put forward with combined compromise solution formulation for rational selection of biomass production location. The usefulness of the developed framework is testified by using a case example and comparison with extant approaches, revealing the superiorities and limitations of the framework.

Suggested Citation

  • Raghunathan Krishankumar & Arunodaya Raj Mishra & Pratibha Rani & Fausto Cavallaro & Kattur Soundarapandian Ravichandran, 2023. "A Novel Integrated q-Rung Fuzzy Framework for Biomass Location Selection with No Apriori Weight Choices," Sustainability, MDPI, vol. 15(4), pages 1-21, February.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:4:p:3377-:d:1066350
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