What is the difference between the study of Evolutionary algorithm vs. Optimization? I have a course named "Evolutionary Algorithm". But, our teacher is always mentioning the word "Optimization" in his lectures.
I am confused. Is he actually teaching Optimization? If yes, why is the name of the course not "Optimization"?
What is the difference between the study of Evolutionary algorithm and Optimization?
 A: Yes, you are correct, your lecturer is teaching (a subset of) Optimisation techniques. That said, it is a good choice of him to emphasise that the class is about Evolutionary Algorithms instead of "standard" Optimisation approaches.
Usually a "standard" first course on Optimisation involves the study of convergence criteria/conditions (e.g. Wolfe conditions), use of gradients (e.g. BFGS) and Hessians (eg. Newton's method) before touching more advanced concepts like constrained optimisation, combinatorial optimization, etc. Evolutionary algorithms are primarily (meta-)heuristics approaches closely associated with genetic algorithms and/or stochastic optimisation (e.g. Simulated annealing), that work with a population-of-solutions notion. This is contrast with the "standard" Optimisation approach where we have a single "best" solution and we update it in an iterative manner.
Both approaches ultimately try to solve the same problem (minimise a particular cost function) but employ very different approaches. 
