Editorial Statement

Oktay Günlük, Editor-in-Chief

INFORMS Journal on Optimization (IJOO) welcomes papers that address all aspects of mathematical optimization, including optimization theory, algorithms, software, computational practice, applications, and the connections between these areas. The journal spans a wide spectrum of topics, encompassing both theoretical and computational issues, as well as application studies.

The journal covers a diverse range of methodologies, including convex optimization (e.g., linear optimization), general-purpose nonlinear optimization, discrete optimization (e.g., combinatorial, integer, mixed-integer optimization), optimization under uncertainty (e.g., dynamic programming, stochastic programming, robust optimization, simulation-based optimization), online optimization, and approximation algorithms. Additionally, contributions to the intersection of optimization and machine learning that are particularly relevant to decision-making and operations research are encouraged.

The journal also invites submissions that study significant and novel applications of optimization. Example application areas include healthcare, inventory and supply chain management, logistics, revenue management and pricing, energy, interfaces with computer science, quantum computing, and finance.

While there is no strict page limit, authors are strongly encouraged to submit papers that are 30 pages or fewer, including appendices.

Papers that have previously appeared in conference proceedings will also be considered, provided they meet the journal's standards. IJOO additionally publishes special issues on topics of current interest to the optimization community, with each issue managed by one or more guest editors.