Inspired by nature, many types of Population based metaheuristics or P-metaheuristics is cropping out of research labs to help solve real life problems. Since every metaheuristics has its own strength and weaknesses, hybridizing the algorithms can sometimes produce better results. To this date of literature, Low-level Teamwork Hybridization is considered as an effective and popular method for hybridization of P-metaheuristics. In many cases however, the approach might prove to be quite complicated. The hybridization often requires metaheuristics internal structure modification in order for the different algorithms to fit well together. Another difficulty is in determining which strategies to be retained and which to be dropped or replaced in each of the metaheuristic algorithms. This paper provides a general abstraction for P-metaheuristics and describes the main P-metaheuristics components that are suitable candidates for hybridization. The review and comparative study of several implementations of Low-level Teamwork Hybridization is also presented. © 2011 IEEE.