JUCS - Journal of Universal Computer Science 14(15): 2471-2490, doi: 10.3217/jucs-014-15-2471
Parallel Strategies for Stochastic Evolution
expand article infoSadiq M. Sait‡, Khawar S. Khan‡, Mustafa I. Ali‡
‡ King Fahd University of Petroleum & Minerals, Dhahran, Saudi Arabia

Corresponding author: Sadiq Sait ( sadiq@kfupm.edu.sa )

© Sadiq Sait, Khawar Khan, Mustafa Ali.
This article is freely available under the J.UCS Open Content License.
Citation: Sait SM, Khan KS, Ali MI (2008) Parallel Strategies for Stochastic Evolution. JUCS - Journal of Universal Computer Science 14(15): 2471-2490. https://doi.org/10.3217/jucs-014-15-2471
Open Access
Abstract
This paper discusses the parallelization of Stochastic Evolution (StocE) metaheuristic, for a distributed parallel environment. VLSI cell placement is used as an optimization problem. A comprehensive set of parallelization approaches are tested and an effective strategy is identified in terms of two underlying factors: workload division and the effect of parallelization on metaheuristic's search intelligence. The strategies are compared with parallelization of another similar evolutionary metaheuristic called Simulated Evolution (SimE). The role of the two mentioned underlying factors is discussed in parallelization of StocE.
Keywords
parallel metaheuristics, combinatorial optimization, stochastic evolution, simulated evolution, VLSI cell placement, cluster computing