Development of a mathematical model for optimal planning of biofuel supply chain

Biofuels have attracted the attention of researchers, due to their potential to mitigate climate changes. Biodiesel is a type of biofuel that can be used as an alternative fuel for diesel engines. The three main problems with biodiesel production are, high production costs, environmental, and soc...

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Bibliographic Details
Main Author: Valizadeh, Maryam
Format: Thesis
Language:English
Published: 2014
Online Access:http://psasir.upm.edu.my/id/eprint/64387/1/FK%202014%20146IR.pdf
http://psasir.upm.edu.my/id/eprint/64387/
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Summary:Biofuels have attracted the attention of researchers, due to their potential to mitigate climate changes. Biodiesel is a type of biofuel that can be used as an alternative fuel for diesel engines. The three main problems with biodiesel production are, high production costs, environmental, and social impact over the entire supply chain. The main objective of this thesis is to propose a method for optimal planning and operation of biodiesel supply chain. An additional objective is to understand the capability of a modern heuristic method for optimal planning of the chain. In this study, a methodology is presented to optimize the full supply chain for producing biodiesel. A Multi-Objective Linear Programming (MOLP) model is developed, which takes into account the economic, environmental and social concerns that are related to the biodiesel supply chain. The model aims to minimize total operational cost, greenhouse gas (GHG) emission, and edible feedstock consumption. The proposed model is solved using a simple MultiObjective Particle Swarm Optimization (MOPSO) method, to overcome the difficulties related to classical methods for solving multi-objective optimization problems. The performance of this method is compared with a well-known classical method, Ɛ-constraint, to study the capability of the MOPSO method. The proposed model and solving strategy was used to evaluate biodiesel production from palm oil and jatropha, based on existing biodiesel plants in Malaysia. The results show that the MOPSO method has a good ability for finding the approximation of optimal solutions. The model determined the optimal annual operational cost, GHG emission, edible feedstock consumption, quantity of feedstock to be harvested, transportation schedules, and quantity of biodiesel to be produced at bio-refineries, for the selected case study in Malaysia. The model was also compared with an economic and environmentaleconomic optimization models. The results show the effectiveness of the proposed MOLP model at providing decisions with better economic, environmental, and social performances. Furthermore, a sensitivity analysis, based on the availability of jatropha, demonstrated the impact of a reduction of jatropha availability, on total emission and edible feedstock consumption.