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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| Main Author: | |
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| Format: | Thesis |
| Language: | English |
| Published: |
2014
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| Subjects: | |
| Online Access: | http://psasir.upm.edu.my/id/eprint/64387/1/FK%202014%20146IR.pdf |
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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. |
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