Climate change and optimal energy technology R\&D policy
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Publication:545123
DOI10.1016/j.ejor.2011.03.046zbMath1215.91062OpenAlexW2027010621WikidataQ112606035 ScholiaQ112606035MaRDI QIDQ545123
Publication date: 22 June 2011
Published in: European Journal of Operational Research (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.ejor.2011.03.046
Stochastic programming (90C15) Environmental economics (natural resource models, harvesting, pollution, etc.) (91B76) Resource and cost allocation (including fair division, apportionment, etc.) (91B32)
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Uses Software
Cites Work
- Inference of statistical bounds for multistage stochastic programming problems
- The empirical behavior of sampling methods for stochastic programming
- The Sample Average Approximation Method for Stochastic Discrete Optimization
- Increasing Risk and Increasing Informativeness: Equivalence Theorems
- Maximizing Submodular Set Functions: Formulations and Analysis of Algorithms
