We invite researchers to contribute to a collection in Computational Management Science focusing on Stochastic Optimization. The collection is connected to the 2nd Copenhagen School of Stochastic Programming (25th-28th June 2024, Copenhagen) and to the joint ECSO-CMS conference (4th-5th July 2024, Stockholm). This collection aims to showcase cutting-edge methodology as well as contemporary applications in the field.
Scope:
We welcome submissions that span a wide spectrum, encompassing both methodology and practical applications of stochastic optimization. Papers must be within the realm of Stochastic Programming, Distributionally Robust Optimization and Stochastic Programming with Decision-Dependent Uncertainty. Particularly, the special issue welcomes:
• Methodology papers. These papers must contribute to the state-of-the-art. Topics may include, for example, new solution algorithms or advancements in existing algorithms (with particular emphasis on exact methods), approximation methods (e.g. scenario generation methods), and bounding techniques. Submissions should provide theoretical insights, algorithmic details, and demonstrate the potential impact on practical problem-solving.
• Papers showcasing modern applications of stochastic optimization. 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. Of particular interest are papers illustrating modern applications of risk-averse stochastic optimization (e.g., the effect of introducing risk measures, time consistency issues).
For more invormation please visit https://link.springer.com/collections/iiejhcbaee.
The guest editors Giovanni Pantuso, Trine Boomsma and Francesca Maggioni.