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1 |
Pricing decisions in a decentralized biofuel supply chain with RIN mechanism considering environmental impacts
تصمیمات قیمت گذاری در زنجیره تأمین سوخت زیستی غیرمتمرکز با مکانیسم RIN با در نظر گرفتن تأثیرات زیست محیطی-2021 This study develops pricing models in a decentralized biofuel supply chain focusing on both economic and environmental aspects. Environmental impacts are used as a measure to reflect the environmental objective function calculated based on ReCiPe method. A bi-level multi-objective stackelberg game model considering farmers and biorefineries as followers and the blender as leader is proposed. An ε-constraint method is utilized to convert the multi-objective model to a single-objective one. The bi-level model is then transformed to a solvable integrated model. Finally, a real case study of switchgrass bioethanol is presented to illustrate the performance of the proposed model. Results show that focusing on environmental goals results in the increasement of selling prices and profits of farmers and biorefineries and decreasment of about %7 in economic profit of the blender. Therefore, tradeoff analyses are performed for objective functions leading to 10 Pareto optimal solutions which give managerial insights to the blender. Moreover, sensitivity analyses are provided with respects to price elasticity and final fuel’s price and results show logical trends in selling prices. Keywords: Biofuel supply chain | Pricing | Decentralized decision making | Environmental impacts | Multi-objective optimization |
مقاله انگلیسی |
2 |
An integrated data envelopment analysis-mathematical programming approach to strategic biodiesel supply chain network design problem
رویکرد برنامه ریزی تجزیه و تحلیل یکپارچه داده ها و ریاضی به مسئله طراحی شبکه شبکه زنجیره تامین استراتژیک-2017 Global warming, environmental issues, food crisis and energy security are the main concerning problems
which have triggered a sense of urgency among policymakers and development practitioners to find
sustainable and viable solutions in the area of bioenergy. Among various edible and non-edible bio
energy feedstocks specified for biodiesel production, Jatropha curcas L. (JCL) and waste cooking oil (WCO)
have been introduced to be promising and sustainable. In this study, an integrated hybrid approach based
on a data envelopment analysis (DEA) and mathematical programming techniques is presented for the
strategic design of biodiesel supply chain network in Iran. In the first phase, JCL cultivation areas are
assessed according to climatic and social criteria by a unified DEA (UDEA) model. In the second phase, the
locations which have achieved desired efficiency scores are considered as candidate locations for JCL
cultivation within a mathematical programming model developed for designing the biodiesel supply
chain network. The proposed mathematical programming model optimizes the numbers, locations and
capacities of JCL cultivation centers, JCL seeds and WCO collection centers, bio-refineries, and distribution
centers. The proposed approach is implemented in Iran for 10 years planning horizon. The results show
the usefulness and efficiency of the proposed method in assisting the policymakers to take suitable
strategic and tactical level decisions related to biodiesel supply chain planning.
Keywords: Jatropha curcas L | Biofuel supply chain optimization | Data envelopment analysis | Mathematical programming techniques | Sustainable | development |
مقاله انگلیسی |
3 |
Resiliency optimization of biomass to biofuel supply chain incorporating regional biomass pre-processing depots
بهینه سازی انعطاف پذیری زیست توده به زنجیره تامین سوخت زیستی با استفاده از انبارهای پیش پردازش زیست توده منطقه ای-2017 Biomass to biofuel supply chain is subject to several potential disruptions such as flood, drought, pest
attack, and equipment failure. These disruptions must be considered while designing the supply chain;
especially if capital cost intensive components such as regional biomass pre-processing depots (RBPD)
are to be implemented. This work develops a supply chain design optimization model that incorporates
the possibility of such disruptions at the design stage. The objective function is the sum of the total cost
incurred during the non-disruption and disruption scenarios weighted by their respective probability of
occurrence. This also quantifies the expected disruption cost (EDC) on the operation of the supply chain.
The decision variables are the locations and capacities of RBPDs and biorefinery, as well as the biomass
flow across the supply chain. The model was applied to two separate case studies, namely, procurement
of corn stover from farms arranged in a generic grid pattern, and procurement of corn stover, switch
grass, and Miscanthus for a region of thirteen counties in Southern Illinois. The simulation results
showed that the consideration of resiliency in design reduced the EDC of supply chain by up to 38% by
optimizing the RBPD locations. The results were shown to depend on the intensity and nature of dis
ruptions. This was especially true for feedstock with higher yield such as Miscanthus. Local parameters
such as yield and biomass price also affected the optimal results. Moreover, the presence of RBPDs was
shown to increase supply chain resiliency.
Keywords:Biomass supply chain|Disruption|Resiliency|Optimization|Pre-processing|Biorefinery|Cost analysis |
مقاله انگلیسی |
4 |
A sustainable second-generation biodiesel supply chain network design problem under risk
مشکل طراحی نسل دوم شبکه زنجیره تامین بیودیزل پایدار در معرض خطر-2017 This paper presents a multi-objective possibilistic programming model to design a second-generation
biodiesel supply chain network under risk. The proposed model minimizes the total costs of biodiesel
supply chain from feedstock supply centers to customer centers besides minimizing the environmental
impact (EI) of all involved processes under a well-to-wheel perspective. Non-edible feedstocks are
considered for biodiesel production. Variable cultivation cost of non-edible feedstock is assumed to be
non-linear and dependent upon the amount of cultivated area. New formulation of possibilistic pro
gramming method is developed which is able to minimize the total mean and risk values of problems
with possibilistic-based uncertainty. To solve the proposed multi-objective model, a hybrid solution
approach based on flexible lexicographic and augmented ɛ-constraint methods is proposed which is
capable to find appropriate efficient solutions from the Pareto-optimal set. The performance of the
proposed possibilistic programming method as well as the developed solution approach are evaluated
and validated through conducting a real case study in Iran. The outcome of this study demonstrates that
high investment cost is required for improving the environmental impact and risk of sustainable bio
diesel supply chain network design under risk. Decision maker preferences are required for suitable
trade-off among total costs, risk values and environmental impact.
Keywords: Sustainable development | Second-generation biodiesel supply chain | Non-edible feedstock | Possibilistic programming |Multi-objective optimization |
مقاله انگلیسی |
5 |
A conceptual framework for the analysis of the effect of institutions on biofuel supply chains
چارچوب مفهومی برای تجزیه و تحلیل اثر نهاد ها در زنجیره تامین سوخت زیستی-2017 The economic performance of biofuels supply chains depends on the interaction of technical character
istics as technological pathways and logistics, and social structures as actor behavior, their interactions
and institutions. Traditional approaches focus on the technical problems only. Little attention has been
paid to the institutional analysis of biofuel supply chains. This paper aims to extend the analysis of the
effect of institutions on the emergence of biofuel supply chains by developing a conceptual framework
that combines elements of complex adaptive systems, (neo) institutional economics and socio
technical systems theory. These elements were formalized into an agent-based model. The proposed
method is illustrated by a case study on a biodiesel supply chain in Germany. It was found that the pat
terns in production capacity result from investors basing their decisions on optimistic perceptions of the
market development that increase with a favorable institutional framework. Conversely, patterns in bio
diesel production cannot be completely explained by this mechanism. The proposed framework assisted
the model conceptualization phase and allowed the incorporation of social structures into the agent
based model. This approach could be developed further to provide insights on the effect of different
future deployment strategies on bioenergy systems emergence and development.
Keywords: Complex adaptive systems | (Neo) institutional economics | Socio-technical systems |Agent-based modeling |Biofuel supply chains |
مقاله انگلیسی |