Proceedings Article10.1109/UBMK.2017.8093562
Improved antlion optimization algorithm
Haydar Kilic,Uğur Yüzgeç +1 more
- 01 Oct 2017
pp 84-88
3
TL;DR: The improved antlion optimization algo-rithm (IALO) is presented and it is understood that it is more successful than the ALO in the tests for high dimensional benchmark functions.
read more
Abstract: In this study, improved antlion optimization algo-rithm (IALO) is presented. The antlion optimization algorithm (ALO) is an heuristic optimization algorithm based on modeling random walks of ants and hunting ants by antlions. The random walk model of ALO and the IALO revealed by improvements in the selection method have been tested with benchmark functions with different characteristics from the literature. The proposed algorithm is compared with different metrics (accuracy, optimality, best average solution, CPU time, etc.) with particle swarm optimization (PSO), artificial bee colony (ABC) and ant lion optimization algorithm (ALO). The IALO algorithm has an optimal result in a shorter time than the ALO, and it is understood that it is more successful than the ALO in the tests for high dimensional benchmark functions.
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
Citations
Ant Lion Optimization: Variants, Hybrids, and Applications
TL;DR: This comprehensive study, which categorized the recent versions of ALO into 3 Categories mainly Modified, Hybrid and Multi-Objective, introduces an introduction about ALO and gives a conclusion of the main ALO foundations.
Tournament selection based antlion optimization algorithm for solving quadratic assignment problem
Haydar Kilic,Uğur Yüzgeç +1 more
TL;DR: The tournament selection method instead of the roulette wheel method on random walking mechanism of ALO and some equations used in ALO algorithm are updated and this version has the best performance in comparison with those of the other meta-heuristic algorithms.
Image Compression Using Different Optimization Algorithms: A Review
Salma Gaber Abbas,Tarek Hassan Mohamed +1 more
TL;DR: This review assesses image compression techniques using various optimization algorithms, highlighting the need for efficient storage and transmission, and evaluating the performance of a proposed algorithm that outperforms existing methods in terms of PSNR and compression bit rate.
References
Particle swarm optimization
James Kennedy,Russell C. Eberhart +1 more
- 06 Aug 2002
TL;DR: A concept for the optimization of nonlinear functions using particle swarm methodology is introduced, and the evolution of several paradigms is outlined, and an implementation of one of the paradigm is discussed.
44.1K
Particle Swarm Optimization.
James Kennedy
- 01 Jan 2017
TL;DR: A concept for the optimization of nonlinear functions using particle swarm methodology is introduced, and the evolution of several paradigms is outlined, and an implementation of one of the paradigm is discussed.
35K
Particle swarm optimization
TL;DR: A snapshot of particle swarming from the authors’ perspective, including variations in the algorithm, current and ongoing research, applications and open problems, is included.
The Ant Lion Optimizer
TL;DR: The results of the test functions prove that the proposed ALO algorithm is able to provide very competitive results in terms of improved exploration, local optima avoidance, exploitation, and convergence, showing that this algorithm has merits in solving constrained problems with diverse search spaces.
3K