We are pleased to announced the modified description and title of this area (led by Pascal Van Hentenryck) of
INFORMS Journal on Computing to emphasize the computational aspect.
Computational Modeling: Methods and Analysis
Rapid advances in computing technology have permitted the solution of increasingly large and complex operations research models. As a consequence, much greater attention must be paid to formulation and modeling issues. This includes the need to understand how to model complex problems effectively, how to compare formulations, and how to find the proper tradeoffs between model fidelity and the required computational resources to solve it. The area also covers the need for novel techniques and tools for acquiring, formulating, debugging, analyzing, and visualizing models. Modeling Methods and Model Analysis are the two main overlapping themes in this very broad area: Modeling Methods covers research on ways of creating and managing operations research models which features a significant computational component. It includes computational techniques to model uncertainty, represent complex data sets and solutions, and capture complex decisions, objectives, and constraints. It also covers techniques to acquire constraints and elucidate preferences, algebraic modeling languages, and graphical representations. Moreover, this theme includes how to formulate and compare models for highly complex applications, trading off model fidelity and computational requirements. Model Analysis covers research on ways to analyze models and model instances to provide useful insights. Examples include computational methods and tools for explaining, debugging, visualizing, and analyzing models. It also covers techniques for reformulating and simplifying models, and for infeasibility analysis.
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Alice Smith
Editor in Chief, INFORMS Journal on Computing
Forehand/Accenture Distinguished Professor
Auburn University
Auburn AL
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