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A New Efficient Meta-Heuristic Optimization Algorithm Inspired by Wild Dog Packs
Essam Al Daoud,Rafat Alshorman,Feras Hanandeh 보안공학연구지원센터 2014 International Journal of Hybrid Information Techno Vol.7 No.6
Although meta-heuristic optimization algorithms have been used to solve many optimization problems, they still suffer from two main difficulties: What are the best parameters for a particular problem? How do we escape from the local optima? In this paper, a new, efficient meta-heuristic optimization algorithm inspired by wild dog packs is proposed. The main idea involves using three self-competitive parameters that are similar to the smell strength. The parameters are used to control the movement of the alpha dogs and, consequently, the movement of the whole pack. The rest of the pack is used to explore the neighboring area of the alpha dog, while the hoo procedure is used to escape from the local optima. The suggested method is applied to several unimodal and multimodal benchmark problems and is compared to five modern meta-heuristic algorithms. The experimental results show that the new algorithm outperforms other peer algorithms.
Power Aware Ant Colony Routing Algorithm for Mobile Ad-hoc Networks
Alaa E. Abdallah,Emad E. Abdallah,Feras Hanandeh,Ashraf Aljammal,Essam Al-Daoud 보안공학연구지원센터 2015 International Journal of Software Engineering and Vol.9 No.12
Due to the limited lifetime of nodes in ad hoc and sensor network, energy efficiency needs to be an important design consideration in any routing algorithm. Most of the existing Ant colony based routing algorithms grantee the packet delivery. However, they suffer from the high power consumption due to the huge number of control messages to establish and maintain a route from a source to a destination. This paper introduces two new power-aware ant colony routing algorithms for mobile ad hoc network under three main concurrent constraints. (1) Localized algorithms where only information about neighbors' nodes is needed. (2) Maximize the algorithms delivery rate. (3) Minimize the energy consumption. Our new algorithms are based on the idea of extracting a sub-graph of the original network topology and combine it with the advantage of ant based routing algorithms. Extensive experiments are conducted to prove that the new algorithms have significant improvement on the network lifetime (up to twice) without affecting the high delivery rate.