ABSTRACT
Invariably all optimization problems carry constraints, and examples can be given from any area one can think of. The supply of a product is constrained by the capacity of a machine. The trajectory of a rocket is constrained by the final target as well as the maximum aerodynamic load it can carry. The range of an aircraft is constrained by its payload, fuel capacity, and its aerodynamic characteristics. So how does a constrained optimization problem differ from an unconstrained problem? In constrained optimization problems, the feasible region gets restricted because of the presence of constraints. This is more challenging because for a multivariable problem with several nonlinear constraints, arriving at any feasible point itself is a daunting task.
