Applications of Equilibrium Modeling and Game Theory in Biomass Supply Chain Management
Bibliographic record
Abstract
The increasing attention towards renewable energies as solutions to environmental problems and future energy security has made biomass-based energy an attractive option. Biomass energy not only reduces dependence on fossil fuels but also helps mitigate environmental impacts. Effective biomass supply chain management is essential for bioenergy production, covering the entire process from feedstock harvesting to energy conversion facilities. Despite its advantages, biomass-based energy faces challenges such as low energy density, seasonal availability, and variable costs. Moreover, inefficient interactions and conflicting interests among supply chain participants hinder its development. \nTo address these challenges, efficient decision-making structures and coordination among supply chain entities are crucial. This PhD thesis focuses on coordination in biomass supply chains using game theoretical tools, which are well-suited for addressing conflicting objectives. The research encompasses three main attempts: \n1.\tEvaluation of the impact of power distribution on supply chain efficiency through game theoretic modeling, considering various leadership schemes. \n2.\tAssessment of the role of government incentives using game theoretic analysis to determine the most effective approach for incentivizing biomass development. \n3.\tDesign of game theoretic contract approaches for coordinating biomass supply chains while considering environmental impacts, including revenue sharing and quantity discounts. \nNon-cooperative approaches, particularly Stackelberg game and equilibrium models, are emphasized within the game theoretic framework. A case study of northern Canadian communities is proposed to validate the feasibility of replacing diesel with bioenergy for heat and electricity consumption. \nPreliminary work on modeling supply chains with different leaders using Stackelberg games has shown promising results, demonstrating the dominant role of communities in supply chain efficiency. The outcomes of this research have been published in peer-reviewed journals, including Sustainable Cities and Society and Clean Technologies and Environmental Policy. Additionally, a coordinated approach involving quantity discounts and revenue sharing has been proposed to evaluate the economic and environmental impact of bioenergy development. This approach has shown potential for improved economic performance and significant reductions in environmental impact. By employing game theory and coordination strategies, this thesis contributes to the understanding and optimization of biomass supply chains, promoting sustainable energy systems and addressing the challenges faced in the bioenergy sector.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".