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Dear colleagues,
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<div>We would like to invite you to contribute to a special issue of <b>Computational Management Science</b> with the title “<a href="https://link.springer.com/collections/iiejhcbaee"><i><b>Stochastic Optimization: Methodological Advancements and Modern Applications</b></i></a>”.</div>
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<div>The special issue welcomes submissions within the realm of Stochastic Programming, Distributionally Robust Optimization and Stochastic Programming with Decision-Dependent Uncertainty. Particularly, the special issue welcomes two types of papers:</div>
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<div>- <b>Methodology papers</b>. These contribute to the state-of-the-art with, for example, new solution algorithms, advancements in existing algorithms, approximation methods, bounding techniques. Submissions should provide some theoretical insights, algorithmic
details, and demonstrate the potential impact on practical problem-solving.</div>
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<div>- <b>Papers showcasing modern applications of stochastic optimization</b>. These papers must illustrate how stochastic optimization contributes to contemporary management science scenarios. Submissions should emphasize novel and unexplored real-world problem-solving,
highlighting the relevance and effectiveness of stochastic optimization in diverse domains. </div>
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<div>The submission deadline is 31st December. </div>
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<div>You are very welcome to contact the guest editors for any additional information :</div>
<div>- Trine Boomsma: <a href="mailto:trine@math.ku.dk">trine@math.ku.dk</a></div>
<div>- Francesca Maggioni: <a href="mailto:francesca.maggioni@unibg.it">francesca.maggioni@unibg.it</a></div>
<div>- Giovanni Pantuso: <a href="mailto:gp@math.ku.dk">gp@math.ku.dk</a></div>
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