Though many use the word optimization as a vacuous buzzword, the term is directly related to operations research. Optimization, whose problems can be described as linear or non-linear, is the process and the computational procedures devised to find the policy under which the model, describing the problem, achieves its best value while satisfying all constraints. One may say that optimization is the method for calculating the best possible utilization of resources (people, time, processes, vehicles, equipment, raw materials, supplies, capacity, securities, etc.) needed to achieve a desired result, such as minimizing cost or process time or maximizing throughout, service levels, or safety.

In other words, the optimization process finds the best alternative among the myriad of alternatives, something that cannot be achieved by enumeration of all alternatives for meaningful problems. As illustrated in an example, optimization improves decision-making speed and quality by providing businesses with responsive, accurate solutions. Optimization utilizes mathematics and computer science techniques to solve complex problems whose results depend on hundreds, thousands, or even millions of interconnected variables.

In general, resource optimization tends to deliver a high return on investment. A major function of management science models and their optimization techniques is in this area and every year thousands of companies and organizations achieve enormous cost savings by utilizing these tools.

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In addition to quantifiable cost savings, optimization can benefit businesses in many ways, as it:

• Finds the best policy among a myriad of alternatives
• Generates solutions faster than any other software
• Automates a solution process and verifies that the solution adheres to the company's business rules
• Dramatically improves business flexibility, responsiveness to changing circumstances, and the ability to test "what if" scenarios
• Focuses decisions and resources on business priorities
• Allows managers to focus on proactive planning instead of last minute reacting