Optimization is today one of the most important tools in implementing and planning efficient operations and increasing competitive advantage. Organizations need to make intelligent decisions to obtain optimal use of their available resources, such as manpower, equipment, raw materials and capital. The discipline of optimization, through the use of advanced mathematics and computer science techniques, can be used to assist organizations with solving their complex business problems in areas such as manufacturing, distribution, finance, and scheduling. Typically, these optimization problems contain hundreds, thousands, or even millions of interconnected variables and require an advanced set of software tools to solve.
Today, the field of optimization entails highly advanced software applications that integrate sophisticated mathematical algorithms and modeling techniques with intelligent software programming and data processing capabilities.
Optimization projects begin with the development of a mathematical model that defines the business problem. Individual business decisions are represented as “variables,” and the connections between them are represented by a series of mathematical equations termed “constraints”. The “objective” represents the goal of the business problem, for example, to maximize profitability or lower costs. Identifying the variables, the constraints and the objective is known as the “modeling” process and is an essential task for every optimization project. After the model has been formulated, it is then solved, using an optimization solver, which, at its core, has highly sophisticated algorithms adept at intelligently sorting through huge amounts of data and analyzing possible approaches to come up with an optimal solution.