Introduction

Optimization is the scientific management of controllable operating/operational parameters to maximize productivity, profitability, and performance, within the imposed internal/external constraints. In any business activity, a number of conflicting parameters exert their influence on the products/services provided by the organization. Hence, the organization chief has to make appropriate decisions on what must be done to maximize the performance in a given situation. This leads to an optimization problem(s), with three basic components: objective function, variables, and constraints.

An objective function is one that needs to be minimized or maximized. For instance, in a power plant in which a number of boilers are operating in open cycle and cogeneration mode, the objective function is to generate power to meet the demand at lowest operating cost and maximum profit. By use of experimental data, it is possible to develop a user-defined model, which will minimize the total deviation of observed data from the predicted model output. In this problem, the variables include boiler capacity, turndown ratio, turbine load, turbine efficiency, fuel cost, steam cost, and total operating cost for a particular mode of operation. A set of constraints allow the unknowns to take on certain values but exclude others. In this power plant problem, the constraints include individual boiler load, boiler maximum efficiency point, turbine load, and turbine efficiency point.

The optimization problem is then narrowed down to find the values of the variables that minimize or maximize the objective function as required, while fulfilling all the constraints.