A Robust Possibilistic Bi-Objective Mixed Integer Model for Green Biofuel Supply Chain Design under Uncertain Conditions

Abstract

In recent years, concerns regarding issues such as climate change, greenhouse gas emissions, fossil reserve dependency, and petroleum price fluctuation have led countries to focus on renewable energies. Meanwhile, in developing countries, designing an appropriate biofuel supply chain network regarding environmental competencies is an important problem. This paper presents a new bi-objective mixed integer mathematical model aiming to minimize CO2 emission and total costs in the process of the biofuel supply chain, creating a suitable green supply chain network. In this respect, CO2 emission and biofuel demand are regarded as uncertain data to address the real complex cases. Moreover, the SAUGMECON approach was implemented to construct a single objective model, and the obtained Pareto optimal points were depicted and analyzed. Thereby, a robust possibilistic programming approach was implemented to the proposed model to handle existing imprecise data. Furthermore, the applicability and performance of the proposed model were demonstrated based on an experimental example. In this respect, the obtained results from the proposed robust possibilistic programming model were compared with its crisp form to show the robustness and reliability of the proposed uncertain mathematical model.

Towards facing uncertainties in biofuel supply chain networks: a systematic literature review

“…Therefore, we defined them as hybrid techniques since they involved at least two combinatorial methods. The first class, which has accounted for a significant percentage, used fuzzy sets in conjunction with robust (Ghaderi et al 2018 ; Habib et al 2021 , 2020 ; Mousavi Ahranjani et al 2018 ; Savoji et al 2022 ) and stochastic optimization techniques (Alizadeh et al 2019 ). Such techniques have the ability to model the problem when there are several parameters with different uncertain natures (i.e.…”

Robust design of a logistics system using FePIA procedure and analysis of trade-offs between CO2 emissions and net present value

“…Robust possibilistic programming approaches for supply chain design have been hardly studied by Refs. [ [50] , [51] , [52] , [53] , [54] , [55] ]. In the work [ 50 ], the authors introduce a s biogas supply chain network design model considering the triple bottom line approach.…”

“…The objective function is minimizing the total supply chain cost by reducing carbon emissions. The work [ 52 ] proposes a multiobjective mathematical model considering the minimization of the total CO2 emissions and the total cost of the supply network. A robust possibilistic approach has been proposed to handle existing inaccurate data.…”

Hybrid Optimization of Green Supply Chain Network and Scheduling in Distributed 3D Printing Intelligent Factory

“…Production planning, capacity decision making and outsourcing are all long-term problems, and changes in decision making and demand have a great impact on costs [5,[21][22][23][24]. Supply chain operation and control problems still need to be solved after decision making, such as short-term planning and production decisions, so we need to design supply chain networks to achieve personalized production in order to reduce costs [25][26][27]. On the other hand, with the increasingly serious environmental problems in the world, the construction of a green supply chain system is an important means to promote national development [28][29][30], and reducing carbon emissions has become a factor that must be considered in supply chain design [31][32][33].…”