Classical Optimization Algorithms can be defined as "COA is defined as that algorithm which can be used to identify the best solution from a set of available solutions which is continuous and differentiable. "
Although due to the limitations like the requirement of continuous and differentiable functions such algorithm can not be applied for various objectives however due to the iteration time and optimization efficiency the following five COA is used widely including practical and real-life problems :
Linear programming: Both Objective and Constraint function is represented by a linear function.
Integer programming: Uses linear programs in which at least one variable uses only integer values.
Dynamic programming: here both or anyone's objective or constraint function depends on dynamic functions.
Stochastic programming: Here random function is used to vary the objective function
Quadratic programming: Objective Function is represented by the quadratic function and constraints may be depicted by linear functions
For the complete course on Optimization Techniques: Introduction to Optimization Techniques
or find it at Baipatra.
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