INFORMS Journal on Computing

INFORMS Journal on Computing
Title	INFORMS Journal on Computing
Discipline	Operations research; Computer science
Abbreviation	INFORMS J. Comput.
Publisher	Institute for Operations Research and the Management Sciences
Frequency	Quarterly
History	1989–present
Issn	1526-5528

INFORMS Journal on Computing is a peer-reviewed scholarly journal focusing on the intersection of Operations Research, Optimization, and Computer Science methods applied to decision-making and algorithmic design. The journal is published by the Institute for Operations Research and the Management Sciences and serves as a venue for research connecting theoretical foundations with computational practice relevant to institutions such as the National Science Foundation, the Defense Advanced Research Projects Agency, and the European Research Council. Authors and readers frequently include faculty from universities like Massachusetts Institute of Technology, Stanford University, and University of California, Berkeley, as well as researchers from companies such as Google, IBM, and Microsoft Research.

History

The journal was established in 1989 during a period of growth in computational techniques influenced by advances at institutions like Bell Labs, IBM Research, and Sandia National Laboratories. Early editorial leadership included scholars affiliated with Cornell University, Princeton University, and Northwestern University, reflecting ties to conferences such as the Symposium on Theory of Computing and the ACM SIGACT-SIGOPS community. Over decades the journal evolved alongside milestones like the development of the Simplex algorithm, breakthroughs in Integer programming, and the rise of parallel computing paradigms championed at places like Los Alamos National Laboratory and Argonne National Laboratory.

Scope and Topics

The journal publishes research at the nexus of Operations Research and Computer Science including algorithm design for Network flows, Combinatorial optimization, Approximation algorithms, and Stochastic programming. Typical articles connect theory and computation in settings related to the Traveling Salesman Problem, Vehicle routing problem, Integer linear programming, and methods such as Branch and bound, Cutting-plane method, and Dynamic programming. Applications often touch sectors represented by organizations like FedEx, United Parcel Service, Boeing, and General Electric, and problems arising in contexts such as Supply chain management and Telecommunications studied at centers like Bell Labs and MIT Lincoln Laboratory.

Editorial Board and Peer Review

The editorial structure mirrors practices at journals affiliated with professional societies including the American Mathematical Society, Association for Computing Machinery, and Society for Industrial and Applied Mathematics. Editors-in-chief have historically been drawn from departments at Columbia University, University of Michigan, and University of Pennsylvania and have coordinated associate editors handling submissions on topics from Graph theory to Stochastic optimization. Manuscripts undergo double-blind or single-blind peer review by scholars active at conferences such as International Conference on Machine Learning, NeurIPS, and International Symposium on Mathematical Programming, and by reviewers from research labs like Facebook AI Research and Amazon Web Services.

Publication Details and Metrics

The journal appears quarterly and is distributed to members of the Institute for Operations Research and the Management Sciences as well as institutional subscribers at libraries such as Harvard University Library and British Library. Performance metrics tracked by indexing services include Impact factor and citations recorded in databases like Web of Science, Scopus, and Google Scholar. The editorial office monitors submission-to-decision timelines and acceptance rates comparable to specialized journals such as Mathematical Programming, Operations Research, and Management Science. Special issues have been organized around themes with sponsorship by entities like the National Institutes of Health and the Office of Naval Research.

Notable Articles and Impact

Influential papers published in the journal have advanced algorithmic techniques used in high-profile projects at organizations like NASA, European Space Agency, and Centers for Disease Control and Prevention by addressing problems in Scheduling, Routing, and Data-driven optimization. Some articles have been widely cited alongside foundational works by researchers associated with John von Neumann, George Dantzig, and Richard Karp and have influenced textbooks used at Princeton University Press and Wiley. The journal’s contributions have affected software development in solvers from companies such as Gurobi and CPLEX and inspired open-source projects hosted on platforms like GitHub.

Access and Indexing

Access to articles is available via institutional subscriptions and individual membership in the Institute for Operations Research and the Management Sciences, with availability through databases such as JSTOR, EBSCOhost, ProQuest, and digital archives maintained by university libraries including Stanford University Libraries and University of Cambridge Library. The journal is indexed in bibliographic services such as MathSciNet, INSPIRE-HEP (for applicable computational papers), Emerging Sources Citation Index, and national repositories overseen by agencies like the National Institutes of Health and the National Science Foundation.

Category:Academic journals Category:Operations research