Comparative evaluation of parallelization strategies for evolutionary and stochastic heuristics

Authors:
Sadiq M. Sait;Syed Sanaullah;Ali Mustafa Zaidi;Mustafa I. Ali
Affiliations:
King Fahd University of Petroleum & Minerals, Dhahran, Saudi Arabia;King Fahd University of Petroleum & Minerals, Dhahran, Saudi Arabia;King Fahd University of Petroleum & Minerals, Dhahran, Saudi Arabia;King Fahd University of Petroleum & Minerals, Dhahran, Saudi Arabia
Venue:
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Year:
2005

Citing 2
Cited 1

Iterative Computer Algorithms with Applications in Engineering: Solving Combinatorial Optimization Problems

Iterative Computer Algorithms with Applications in Engineering: Solving Combinatorial Optimization Problems
An evaluation of parallel simulated annealing strategies with application to standard cell placement

IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems

Parallel implementation of evolutionary strategies on heterogeneous clusters with load balancing

IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper we present an evaluation of selected parallel strategies for Simulated Annealing and Simulated Evolution, identifying the impact of various issues on the effectiveness of parallelization. Issues under consideration are the characteristics of these algorithms, the problem instance, and the implementation environment. Observations are presented regarding the impact of parallel strategies on runtime and achievable solution quality. Effective parallel algorithm design choices are identified, along with pitfalls to avoid. We further attempt to generalize our assessments to other heuristics.