  In real life, mostly problems are dynamic. Many algorithms have been proposed
to handle the static problems, but these algorithms do not handle or poorly
handle the dynamic environment problems. Although, many algorithms have been
proposed to handle dynamic problems but still, there are some limitations or
drawbacks in every algorithm regarding diversity of particles and tracking of
already found optima. To overcome these limitations/drawbacks, we have proposed
a new efficient algorithm to handle the dynamic environment effectively by
tracking and locating multiple optima and by improving the diversity and
convergence speed of algorithm. In this algorithm, a new method has been
proposed which explore the undiscovered areas of search space to increase the
diversity of algorithm. This algorithm also uses a method to effectively handle
the overlapped and overcrowded particles. Branke has proposed moving peak
benchmark which is commonly used MBP in literature. We also have performed
different experiments on Moving Peak Benchmark. After comparing the
experimental results with different state of art algorithms, it was seen that
our algorithm performed more efficiently.
