Abstract
In this paper we develop a mathematical model for optimal planning of the biofuel supply chain. The model considers the optimal selection of feedstock while minimizing the total cost and social impact over the planning horizon. A multi-objective linear programming model (MOLP) is proposed to find the optimal solution. A multi-objective particle swarm optimization (MOPSO) method is applied to solve the mathematical model and it is compared with non-dominated sorting genetic algorithm (NSGA-II) . The model is used to evaluate the biodiesel production from palm oil and jatropha in Malaysia.
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Valizadeh, M., Syafiie, S., Ahamad, I.S. (2014). Multi-Objective Particle Swarm Optimization for Optimal Planning of Biodiesel Supply Chain in Malaysia. In: Herawan, T., Ghazali, R., Deris, M. (eds) Recent Advances on Soft Computing and Data Mining. Advances in Intelligent Systems and Computing, vol 287. Springer, Cham. https://doi.org/10.1007/978-3-319-07692-8_28
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DOI: https://doi.org/10.1007/978-3-319-07692-8_28
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-07691-1
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