A Flexible Robust Possibilistic Programming Approach for Sustainable Second-Generation Biogas Supply Chain Design under Multiple Uncertainties

Mohammad Kanan (), Muhammad Salman Habib (), Tufail Habib, Sadaf Zahoor, Anas Gulzar, Hamid Raza and Zaher Abusaq
Additional contact information
Mohammad Kanan: Jeddah College of Engineering, University of Business and Technology, Jeddah 21448, Saudi Arabia
Muhammad Salman Habib: Department of Industrial and Manufacturing Engineering, University of Engineering and Technology, Lahore 54890, Pakistan
Tufail Habib: Department of Industrial Engineering, University of Engineering and Technology, Peshawar 25000, Pakistan
Sadaf Zahoor: Department of Industrial and Manufacturing Engineering, University of Engineering and Technology, Lahore 54890, Pakistan
Anas Gulzar: Department of Industrial and Manufacturing Engineering, University of Engineering and Technology, Lahore 54890, Pakistan
Hamid Raza: Department of Chemistry, University of Management and Technology, C-II Phase 1 Johar Town, Lahore 54770, Pakistan
Zaher Abusaq: Jeddah College of Engineering, University of Business and Technology, Jeddah 21448, Saudi Arabia

Sustainability, 2022, vol. 14, issue 18, 1-32

Abstract: The goal of this research is to develop a novel second-generation-based biogas supply chain network design (BG-SCND) model that takes into account the triple bottom line approach. Biogas is a promising renewable energy source that can be obtained from a variety of easily accessible second-generation wastes, including animal manure, municipal waste, and agricultural leftovers. Integrated optimization of the biogas generation system is essential for a speedy and environmentally friendly transition to sustainable biodiesel production. The dynamic environment of the energy market significantly impairs the decisions of the BG-SCND model; therefore, a hybrid solution approach using flexible programming and possibilistic programming is suggested. To verify the suggested model and approach for solving the problem, a thorough computational analysis of a case study is conducted. The case study findings demonstrate that considerable investment is necessary to attain social and environmental well-being goals and safeguard decisions against epistemic uncertainty. Policymakers involved in the planning of biogas production and distribution projects may find the proposed approach useful.

Keywords: second-generation feedstock; linear programming; biogas supply chain; flexible programming; possibilistic programming (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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