A tag is a keyword or label that categorizes your question with other, similar questions. Using the right tags makes it easier for others to find and answer your question.
For questions related to algorithms expected to produce good solutions, with no guarantee of optimality, in relatively short computation time.
Questions on algorithms that solve mathematical models by generating columns (variables) in the pricing step during solution on demand.
Questions on general heuristic strategies that can be instantiated for a specific problem to obtain a heuristic.
For questions about solving Operations Research problems using the C++ programming language.
For questions on constraints controlled by binary variables.
For questions related to Benders decomposition, a type of optimization algorithm in which certain variables are optimized in a "master problem," the values of those variables are fixed, the remaining …
For questions related to commercial or open-source computer software used for operations research problems.
Questions relevant to the PuLP modelling framework in Python
For questions about solving Operations Research problems using the Java programming language.
Questions on problems whose solution space are one-to-one mappings between two sets.
For questions related to GAMS (General Algebraic Modeling System), a high-level modeling system for mathematical optimization.
For questions related to the knapsack problem that seeks to find the number of each item to include in a limited container (in an integer knapsack or whether to include an item in a binary knapsack),…
For questions related to machine learning (ML), a type of algorithm that attempts to "learn" how to perform a task without being given an explicit set of rules to follow in order to perform it. Questi…
For questions related to the algebraic modeling language AMPL.
For questions on the set of points that satisfy a finite set of linear inequalities.
For questions related to optimization problems for choosing the optimal locations of facilities such as warehouses, factories, fire stations, etc.
Questions related to resources (e.g. data, results, code) that can be downloaded freely from the Internet.
For questions about solving Operations Research problems using Matlab programming language.
For questions related to the branch-and-bound method for integer programming problems, which recursively divides the solution space and identifies upper and lower bounds on the optimal objective funct…
For questions related to the use of computer models to estimate performance measures for complex systems, typically under uncertainty.
For questions about the definition or meaning of terms used within Operations Research. Do not use this tag for questions about notation.
Questions related to the IBM Decision Optimization CPLEX (docplex) which is designed for modeling and solving optimization problems in Python.
For questions on first-order necessary conditions for optimality in non-linear programs due to Karush, Kuhn, and Tucker.
For questions about obtaining upper or lower bounds for certain values, usually for an optimization objective.
For questions related to probability distributions, functions that relate a given value to the likelihood that a random variable will take that value.
For questions about mathematical optimization problems with continuous and discrete variables and nonlinear functions in the objective function and/or the constraints. Should be synonymous with mixed-…
For questions specifically about existence (feasibility), counting feasible points (in a discrete setting), or partitioning the feasible region (e.g. in the context of branch-and-bound methods). Feasi…
For questions about dynamic programming, a mathematical optimization technique where the optimal solution to the problem is found by breaking it down to simpler sub-problems and solved recursively.
for questions relating to an optimal (best) solution which attains the best objective function value over the entire set of feasible solutions.
For questions relating to Operations Research in academic settings.
For questions related to Markov decision processes (MDPs), which model decision making in time-varying and usually stochastic environments.