A two-stage stochastic model for co-firing biomass supply chain networks

Aranguren, Maria; Castillo-Villar, Krystel K.; Aboytes–Ojeda, Mario

doi:10.1016/j.jclepro.2021.128582

Cited by 23 publications

(6 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this case, they solved the multi-objective problem using the weighted sum approach. Aranguren et al, (2021) offered a stochastic hub-and-spoke model and an efficient approach for determining an optimal production, distribution, and transportation network using metaheuristics like Simulated Annealing for NP-hard instances. Samani & Hosseini-Motlagh, (2021) presented a multi-period, multi-product mathematical model to minimize inefficiency, environmental impacts, and supply chain costs.…”

Section: Hybrid Approaches To Biomass-to-bioenergy Supply Chain Designmentioning

confidence: 99%

Stochastic Optimization Approaches to Biomass-to-bioenergy Supply Chain Network Design under Demand Uncertainty

Mohagheghi,

Rezvani,

Hassannayebi

2024

Preprint

View full text Add to dashboard Cite

A critical part of the bioenergy production process is the robust design of the supply chain network. This research proposes robust optimization programming models to design a supply chain network that generates electricity from renewable energy sources under demand uncertainty. The objective is to design a biomass supply chain network that maximizes the profit of a power plant. Given the uncertain electricity demand, a two-stage stochastic programming model is proposed. A hybrid of risk-neutral and risk-averse modeling frameworks is proposed to analyze the alternative biomass-to-bioenergy supply chain design scenarios. The mathematical model has been proven to be effective in justifying the supply chain design based on a case study of the biomass-to-bioenergy supply chain in Iran. The research findings show that the proposed stochastic programming approach outperforms the conventional optimization approaches in terms of solution robustness.

show abstract

Section: Hybrid Approaches To Biomass-to-bioenergy Supply Chain Designmentioning

confidence: 99%

Stochastic Optimization Approaches to Biomass-to-bioenergy Supply Chain Network Design under Demand Uncertainty

Mohagheghi,

Rezvani,

Hassannayebi

2024

Preprint

View full text Add to dashboard Cite

show abstract

“…Furthermore, the supplementary materials highlight the intricacies of various resource flows, encompassing elements such as power, heat, biomass, non-metallic and metallic ores, water, air, CO 2 , labor, and money. Recent shifts in the biomass supply chain literature, moving from linear perspectives to networked approaches [112][113][114], are particularly noteworthy. This paradigm shift facilitates the incorporation of varied resource inflows and product outflows, duly considering residues, by-products, and circular flows intrinsic to the circular bioeconomy.…”

Section: Circular Bioeconomy As a Driver For System Integrationmentioning

confidence: 99%

The circular bioeconomy: a driver for system integration

Schipfer,

Burli,

Fritsche

et al. 2024

Energ Sustain Soc

View full text Add to dashboard Cite

Background Human and earth system modeling, traditionally centered on the interplay between the energy system and the atmosphere, are facing a paradigm shift. The Intergovernmental Panel on Climate Change’s mandate for comprehensive, cross-sectoral climate action emphasizes avoiding the vulnerabilities of narrow sectoral approaches. Our study explores the circular bioeconomy, highlighting the intricate interconnections among agriculture, forestry, aquaculture, technological advancements, and ecological recycling. Collectively, these sectors play a pivotal role in supplying essential resources to meet the food, material, and energy needs of a growing global population. We pose the pertinent question of what it takes to integrate these multifaceted sectors into a new era of holistic systems thinking and planning. Results The foundation for discussion is provided by a novel graphical representation encompassing statistical data on food, materials, energy flows, and circularity. This representation aids in constructing an inventory of technological advancements and climate actions that have the potential to significantly reshape the structure and scale of the economic metabolism in the coming decades. In this context, the three dominant mega-trends—population dynamics, economic developments, and the climate crisis—compel us to address the potential consequences of the identified actions, all of which fall under the four categories of substitution, efficiency, sufficiency, and reliability measures. Substitution and efficiency measures currently dominate systems modeling. Including novel bio-based processes and circularity aspects might require only expanded system boundaries. Conversely, paradigm shifts in systems engineering are expected to center on sufficiency and reliability actions. Effectively assessing the impact of sufficiency measures will necessitate substantial progress in inter- and transdisciplinary collaboration, primarily due to their non-technological nature. In addition, placing emphasis on modeling the reliability and resilience of transformation pathways represents a distinct and emerging frontier that highlights the significance of an integrated network of networks. Conclusions Existing and emerging circular bioeconomy practices can serve as prime examples of system integration. These practices facilitate the interconnection of complex biomass supply chain networks with other networks encompassing feedstock-independent renewable power, hydrogen, CO2, water, and other biotic, abiotic, and intangible resources. Elevating the prominence of these connectors will empower policymakers to steer the amplification of synergies and mitigation of tradeoffs among systems, sectors, and goals.

show abstract

“…Biomass quality is another factor having implications for the planning and design of the supply chain. Biomass quality, such as ash and moisture, impacts the overall cost and topology of the supply chain [91]. It would also be interesting to consider climate and its effects, as climate change is expected to impact soil properties and ecosystems [92].…”

Section: K-means Clusteringmentioning

confidence: 99%

Integrated Land Suitability Assessment for Depots Siting in a Sustainable Biomass Supply Chain

Toba

Paudel

Lin

et al. 2023

Sensors

View full text Add to dashboard Cite

A sustainable biomass supply chain would require not only an effective and fluid transportation system with a reduced carbon footprint and costs, but also good soil characteristics ensuring durable biomass feedstock presence. Unlike existing approaches that fail to account for ecological factors, this work integrates ecological as well as economic factors for developing sustainable supply chain development. For feedstock to be sustainably supplied, it necessitates adequate environmental conditions, which need to be captured in supply chain analysis. Using geospatial data and heuristics, we present an integrated framework that models biomass production suitability, capturing the economic aspect via transportation network analysis and the environmental aspect via ecological indicators. Production suitability is estimated using scores, considering both ecological factors and road transportation networks. These factors include land cover/crop rotation, slope, soil properties (productivity, soil texture, and erodibility factor) and water availability. This scoring determines the spatial distribution of depots with priority to fields scoring the highest. Two methods for depot selection are presented using graph theory and a clustering algorithm to benefit from contextualized insights from both and potentially gain a more comprehensive understanding of biomass supply chain designs. Graph theory, via the clustering coefficient, helps determine dense areas in the network and indicate the most appropriate location for a depot. Clustering algorithm, via K-means, helps form clusters and determine the depot location at the center of these clusters. An application of this innovative concept is performed on a case study in the US South Atlantic, in the Piedmont region, determining distance traveled and depot locations, with implications on supply chain design. The findings from this study show that a more decentralized depot-based supply chain design with 3depots, obtained using the graph theory method, can be more economical and environmentally friendly compared to a design obtained from the clustering algorithm method with 2 depots. In the former, the distance from fields to depots totals 801,031,476 miles, while in the latter, it adds up to 1,037,606,072 miles, which represents about 30% more distance covered for feedstock transportation.

show abstract

A two-stage stochastic model for co-firing biomass supply chain networks

Cited by 23 publications

References 21 publications

Stochastic Optimization Approaches to Biomass-to-bioenergy Supply Chain Network Design under Demand Uncertainty

Stochastic Optimization Approaches to Biomass-to-bioenergy Supply Chain Network Design under Demand Uncertainty

The circular bioeconomy: a driver for system integration

Integrated Land Suitability Assessment for Depots Siting in a Sustainable Biomass Supply Chain

Contact Info

Product

Resources

About