Grey Wolf Optimizer

The Whale Optimization Algorithm

Salp Swarm Algorithm

In this paper a novel nature-inspired optimization paradigm is proposed called Moth-Flame Optimization (MFO) algorithm. The main inspiration of this optimizer is the navigation method of moths in nature called transverse orientation. Moths fly in night by maintaining a fixed angle with respect to the moon, a very effective mechanism for travelling in a straight line for long distances. However, these fancy insects are trapped in a useless/deadly spiral path around artificial lights. This paper mathematically models this behaviour to perform optimization. The MFO algorithm is compared with other well-known nature-inspired algorithms on 29 benchmark and 7 real engineering problems. The statistical results on the benchmark functions show that this algorithm is able to provide very promising and competitive results. Additionally, the results of the real problems demonstrate the merits of this algorithm in solving challenging problems with constrained and unknown search spaces. The paper also considers the application of the proposed algorithm in the field of marine propeller design to further investigate its effectiveness in practice. Note that the source codes of the MFO algorithm are publicly available at http://www.alimirjalili.com/MFO.html.

Moth-flame optimization algorithm

This paper proposes a novel nature-inspired algorithm called Multi-Verse Optimizer (MVO). The main inspirations of this algorithm are based on three concepts in cosmology: white hole, black hole, and wormhole. The mathematical models of these three concepts are developed to perform exploration, exploitation, and local search, respectively. The MVO algorithm is first benchmarked on 19 challenging test problems. It is then applied to five real engineering problems to further confirm its performance. To validate the results, MVO is compared with four well-known algorithms: Grey Wolf Optimizer, Particle Swarm Optimization, Genetic Algorithm, and Gravitational Search Algorithm. The results prove that the proposed algorithm is able to provide very competitive results and outperforms the best algorithms in the literature on the majority of the test beds. The results of the real case studies also demonstrate the potential of MVO in solving real problems with unknown search spaces. Note that the source codes of the proposed MVO algorithm are publicly available at http://www.alimirjalili.com/MVO.html.

Multi-Verse Optimizer: a nature-inspired algorithm for global optimization

On the optimum groove shapes for load-carrying capacity enhancement in parallel flat surface bearings: Theory and experiment

A robust stochastic approach for design optimization of air cooled heat exchangers

Topological and shape optimization of thrust bearings for enhanced load-carrying capacity

http://chglib.icp.ac.ru/subjex/2012/pdf05/ElectrochActa-2012-60(1)55.PDF

A study of the agglomerate catalyst layer for the cathode side of a proton exchange membrane fuel cell: Modeling and optimization

The harmony search (HS) is a music-inspired evolutionary algorithm, mimicking the improvisation process of music players (Geem et al., 2001). The HS is simple in concept, few in parameters, and easy in implementation, with theoretical background of stochastic derivative (Geem, 2007a). The algorithm was originally developed for discrete optimization and later expanded for continuous optimization (Lee & Geem, 2005). The following pseudo code describes how the HS algorithm works: procedure HS // initialize initiate parameters initialize the harmony memory //main loop while (not_termination) for I = 1 to number of decision variables (N) do R1 = uniform random number between 0 and 1 if (R1 < P

/pdf/recent-advances-in-harmony-search-2g2nd1tjf1.pdf

M. Fesanghary

Papers

On the optimum groove shapes for load-carrying capacity enhancement in parallel flat surface bearings: Theory and experiment

A robust stochastic approach for design optimization of air cooled heat exchangers

Topological and shape optimization of thrust bearings for enhanced load-carrying capacity

A study of the agglomerate catalyst layer for the cathode side of a proton exchange membrane fuel cell: Modeling and optimization

Recent Advances in Harmony Search