مشاهده مشخصات مقاله
A Multi-Role Cellular PSO for Dynamic Environments
|
نویسنده (ها) |
-
Ali B. Hashemi
-
M.R. Meybodi
|
|
مربوط به کنفرانس |
چهاردهمین کنفرانس بینالمللی سالانه انجمن کامپیوتر ایران |
|
چکیده |
In real world, optimization problems are usually
dynamic in which local optima of the problem change.
Hence, in these optimization problems goal is not only
to find global optimum but also to track its changes. In
this paper, we propose a variant of cellular PSO, a
new hybrid model of particle swarm optimization and
cellular automata, which addresses dynamic
optimization. In the proposed model, population is
split among cells of cellular automata embedded in the
search space. Each cell of cellular automata can
contain a specified number of particles in order to
keep the diversity of swarm. Moreover, we utilize the
exploration capability of quantum particles in order to
find position of new local optima quickly. To do so,
after a change in environment is detected, some of the
particles in the cell change their role from standard
particles to quantum for few iterations. Experimental
results on moving peaks benchmark show that the
proposed algorithm outperforms mQSO, a well-known
multi swarm model for dynamic optimization, in many
environments. |
|
قیمت |
-
برای اعضای سایت : ۱٠٠,٠٠٠ ریال
-
برای دانشجویان عضو انجمن : ۲٠,٠٠٠ ریال
-
برای اعضای عادی انجمن : ۴٠,٠٠٠ ریال
|
خرید مقاله
|
|
.gif){kind=icon}