Operational (tactical) and strategic mathematical models are used in the optimization decision process to determine more efficient and effective ways to control and manage a system or process. Mathematical models are routinely used in natural sciences (physics, biology), engineering (artificial intelligence, computer science) and social science (economics, political science). However, the lack of agreement between theoretical (mathematical) models and experimental measurement in any discipline often leads to important advances since better theories are developed. Optimization helps create better theories and improves systems/processes in many disciplines. The biggest challenge is to engage the designer, collect the appropriate data and determine the appropriate model (linear vs. nonlinear, deterministic vs. probabilistic, static vs. dynamic or discrete vs. continuous).


Applied Algebra: Solving for Chocolate

Applying algebra in engineering and computer science has a number […]

Computer Architecture

Connect to this wiki page as a companion for the synthesis […]

Economics and Game Theory

Making optimal use of scarce resources is the central theme […]

Mixed-Integer Quadratic Optimization: Algorithms and Complexity

Mixed-integer quadratic programming (MIQP) is the simplest yet arguably the […]


The PATH solver for mixed complementarity problems (MCPs) was introduced […]

Structural properties and strong relaxations for mixed integer polynomial optimization

Research in nonconvex nonlinear programming (NLP) and mixed-integer nonlinear programming […]

Supply Chain

Supply Chain Management became a popular term in the mid-1990s […]