Operations research is an interdisciplinary field that applies mathematical modeling, statistical analysis, and optimization to support decision-making in complex systems. It provides quantitative methods for problems such as inventory control, scheduling, logistics, resource allocation, and the design of efficient …
Operations research is an interdisciplinary field that applies mathematical modeling, statistical analysis, and optimization to support decision-making in complex systems. It provides quantitative methods for problems such as inventory control, scheduling, logistics, resource allocation, and the design of efficient processes, using tools including linear and nonlinear programming, optimization under constraints, and sensitivity analysis. By representing a problem as a model and searching systematically for the best feasible solution, operations research helps organizations improve efficiency, reduce cost, and make informed choices under uncertainty. Within Model Based Research, work relevant to operations research includes a study determining the efficiency of a fuzzy logic economic order quantity inventory model with varying demand, comparing it with Lagrangian and Kuhn-Tucker methods through sensitivity analysis. This research applies optimization techniques to an inventory management problem, illustrating how mathematical models are used to handle demand uncertainty and identify cost-effective ordering policies. This page gathers peer-reviewed, open-access research relevant to operations research and the application of mathematical optimization to practical decision problems.
1 peer-reviewed article, ranked by relevance. Each links to its DOI.
The 1 article above has been cited 19 times in the scholarly literature. Citation data via OpenAlex and Crossref, updated Jun 2026.
A sample of recent works citing this journal's research on Operations Research, linking to each citing work.