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A bi-objective stochastic location-inventory-routing model for microalgae-based biofuel supply chain
- Asadi, Ehsan, Habibi, Farhad, Nickel, Stefan, Sahebi, Hadi
- Applied energy 2018 v.228 pp. 2235-2261
- Taguchi method, algae, algorithms, biofuels, biomass production, carbon dioxide, decision making, fuel production, greenhouse gas emissions, inventories, models, pollution, supply chain, uncertainty, Iran
- This paper introduces a viable two-objective model for the design of algae biofuel production and distribution network with integrated formulation of location, inventory and routing decisions. The model consists of an algae biomass production facility, several distribution facilities, multiple extraction sites, and transport vehicles. In this model, the system implementation cost and its pollution impacts via CO2 emission are considered simultaneously. Our model allows the decision maker to determine the number and location of distribution facilities, the allocation of extraction sites to these facilities, the routes by which extraction sites need to be served, and the minimum inventory level that should be maintained at each distribution facility to achieve the mentioned objectives. In an attempt to bridge the gaps in the literature, the paper tries to incorporate the uncertainty in parameters and also a queueing system into integrated formulation of location, inventory and routing decisions and develop a viable model with economic and environmental objectives considered simultaneously. Since the proposed model belongs to the class of NP-hard problems, two multi-objective metaheuristic algorithms, namely MOPSO and NSGA-II, are tested for solving the formulated model. For this purpose, Taguchi method is used to set the parameters of these algorithms, and then their results are compared in terms of five evaluation criteria. These comparisons show that, for the formulated model, NSGA-II outperforms MOPSO in the majority of evaluation criteria. Finally, the proposed model is evaluated with the real data related to the implementation of an algae biofuel production and distribution network in Iran and the results are further examined. The results demonstrate the good performance of the proposed model.