Global optimization refers to finding the optimal value of a given function among all possible solution whereas local optimization finds the optimal value within the neighboring set of candidate solution.When LINGO finds a solution to a linear optimization model, it is the definitive best solution-we say it is the global optimum. A globally optimal solution is a feasible solution with an objective value that is as good or better than all other feasible solutions to the model.The purpose of optimization is to achieve the “best” design relative to a set of prioritized criteria or constraints. These include maximizing factors such as productivity, strength, reliability, longevity, efficiency, and utilization.This decision-making process is known as optimization.The classical optimization techniques are useful in finding the optimum solution or unconstrained maxima or minima of continuous and differentiable functions. These are analytical methods and make use of differential calculus in locating the optimum solution.The classical optimization techniques are useful in finding the optimum solution or unconstrained maxima or minima of continuous and differentiable functions. These are analytical methods and make use of differential calculus in locating the optimum solution.