چكيده به لاتين
Regarding the developing nature of renewable energy sector, as well as the impact of emerging technologies in the development of biofuel supply chains, one of the most important characteristics of the biofuel supply chain is the substantial role of biofuel production technologies. Besides, another main challenge of bioenergy sector development is the cost of biomass supply chain resulted from inefficient bioenergy production from low energy content biomass feedstocks, high logistics costs of biomass production, handling and transportation. In other words, exploration of new technologies and sources, as well as efficient SCM of biofuel supply chain are two main aspects to be considered. On the other hand, supply chain sustainability as a holistic perspective of supply chain processes has become a key topic in the sustainability literature in recent years because of increasing concerns about the social and environmental impacts of business processes. Moreover, because of the existence of various uncertainties related to biomass supply, demand, production, transportation, operation, and prices, considering deterministic assumptions for parameters in the related optimization problems can result in either infeasible supply chain designs or suboptimal solutions.
Accordingly, in this thesis considering sustainability, uncertainty and the role of biofuel production technologies are proposed to be considered in the design and planning of biofuel supply chain. In the first proposed model, to handle different types of uncertainty, including randomness, epistemic and deep uncertainties, a hybrid robust optimization model is proposed which is the first research that proposes a robust optimization approach capable to handle all types of uncertainty in input data. In the second model, a multiobjective mixed-integer linear programming model is proposed to address the optimal design and planning of a lignocellulosic bioethanol supply chain considering a sustainable supply chain optimization framework including economic, environmental, and social objectives. To handle the inherent uncertainty of the input data in the problem of interest, a novel multiobjective robust possibilistic programming approach is developed.
The performance of the proposed models are demonstrated through case studies developed for a biofuel supply chain in Iran. Also, in order to validate proposed approaches in the first and second models, realization models are developed and the results of the deterministic and robust models are analyzed. On the other hand, in order to propose a dynamic supply chain model according to the ambidexterity paradigm called ”ambidextrous supply chain” , considering separate objective functions for exploitation and exploitation dimensions which constitute pillars of ambidexterity paradigm are proposed to be considered in the design and planning of biofuel supply chain.
