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Optimization is an extremely useful technique to calculate the best possible utilization of resources (people, time, cash, capacity, equipment, etc.) to achieve a desired result such as minimizing cost or maximizing profit.

Recent advances in mathematics, combined with rapidly increasing computer power, now make it an essential tool if you are to remain competitive.

The success of any optimization project will however depend on how well the initial underlying model is structured against a given problem. Starting with a desired result "I would like to be very rich" at one extreme or with a model with one variable at the other, will rarely generate the feasible, optimal solution(s) you are looking for.

We need to move deeper into the problem and typical applications from long to short term, strategic to tactical, include:

Finance/Investment - Working Capital Management, Capital Budgeting, Portfolio and Trade Risk Optimization etc.

Manufacturing - Planning/Scheduling, Rules/Methods Optimization, Product Mix, Blending etc.

Distribution/Networks - Routing, Loading, Vehicle Scheduling, Supply Chain Optimization etc.

A linear programming model is the simplest form of optimization problem and the one that you are most likely to have heard of:

The diagram shows that, within the constraints, maximum profit occurs only when variable x1 = 2 and variable x2 = 6.

Many real-world problems can't be visualized this way because there may well be hundreds or even thousands of variables and constraints - even so, still within the bounds of modern optimization technology.

Please contact Paul Williams with your requirements or questions.