A benders-local branching algorithm for second-generation biodiesel supply chain network design under epistemic uncertainty

Abstract

This paper proposes a possibilistic programming model in order to design a second-generation biodiesel supply chain network under epistemic uncertainty of input data. The developed model minimizes the total costs of the supply chain from supply centers to the biodiesel and glycerin consumer centers. Waste cooking oil and Jatropha plants, as non-edible feedstocks, are considered for biodiesel production. To cope with the epistemic uncertainty of the parameters, a credibility-based possibilistic programming approach is employed to convert the original possibilistic programming model into a crisp counterpart. An accelerated benders decomposition algorithm using efficient acceleration mechanisms is devised to deal with the computational complexity of solving the proposed model in an efficient manner. The performance of the proposed possibilistic programming model and the efficiency of the developed accelerated benders decomposition algorithm are validated by performing a computational analysis using a real case study in Iran.

Modeling and optimizing an agro-supply chain considering different quality grades and storage systems for fresh products: a Benders decomposition solution approach

“…BD algorithm uses the concept of "divide and conquers" to reformulate the original problem into a master problem (MP) and dual subproblem (DSP) in a limited number of iterations. Nowadays, advantages of the BD algorithm, such as a limited number of iterations, less computational time, and guaranteed convergence for largescale problems, make it suitable for many optimization problems (e.g., Pishvaee et al 2010;Shaw et al 2016;Ghezavati et al 2017;Kayvanfar et al 2018;Babazadeh et al 2019;Azadi et al 2019;Mardan et al 2019;Naderi et al 2019;Alkaabneh et al 2020;Gong and Zhang 2021). The primary steps of the BD algorithm work iteratively by outer linearization and relaxation.…”

Optimization Design of a Supply Chain for Jatropha-Based Biofuel from a Sustainable Development Perspective Considering International Resources and Demand: A Case Study

“…The estimated amount of local and foreign demands for biodiesel over the planning horizon is illustrated in Tables and which are taken from Babazadeh et al and Babazadeh et al Iran is a populous country, and more than 75 million liters of gasoline are used daily for its transportation sector according to official statistics. , Therefore, the proposed supply chain is not capable of satisfying such a heavy demand for fuel. In addition, the price of gasoline in Iran is very low compared with European and American countries due to the presence of rich oil resources.…”

A Robust Approach for Cooperation and Coopetition of Bio-Refineries Under Government Interventions by Considering Sustainability Factors

“…The model was developed to support decision-making in production planning to minimize the cost and cost variations in biodiesel production. In order to build a second-generation biodiesel SC network under epistemic input data ambiguity, Babazadeh et al [49] suggested a potential programming model. The developed model minimized the total SC costs from supply centers to market centers for biodiesel and glycerin.…”