Reliable Mobile Ad-Hoc Network Routing Using Firefly Algorithm

Swarm intelligence algorithms are designed to mimic the natural behaviors of living organisms. The birds, animals and insects exhibit extraordinary problem solving behaviors and intelligence when living in colonies or groups. These unique behaviors form the basis for the design of the Metaheuristic which are helpful in solving several real-life combinatorial optimization problems. Monkey algorithm is developed based on the unique behaviors of monkeys such as mountain and tree climbing, jumping, watching and somersaulting. This paper reports for the first time the design and development of Multi-objective Monkey Algorithm (MoMA) and its use for the design of molecules with optimal drug-like properties. Finally, the performance of the proposed MoMA for Drug design (MoMADrug) is compared with the previously disclosed Multi-objective Genetic algorithm (MoGADdrug) for the design of drug-like molecules.

Section: Related Workmentioning

confidence: 99%

Multi-objective Monkey Algorithm for Drug Design

Devi¹,

Sathya²,

Kumar³

et al. 2019

“…f is the four-peak function as illustrated in Fig.1(a), which has two local peaks with 1 f  at ( 4,4)  and (4, 4) , and two global peaks with max 2 f  at (0, 0) and (0, 4)  . Function 2 f is showed in Fig.1(b), which has many local maximum and one global maximum 1 =1 f at ( , ) (0,0)…”

Section: Functionmentioning

confidence: 99%

“…Originated by bioluminescence, a new heuristic intelligence algorithm-firefly algorithm (FA), was developed by Dr. Xin-She Yang at Cambridge University in 2008 [1], with many similarities with other algorithms which are based on the so-called swarm intelligence, such as the famous Particle Swarm Optimization (PSO) [2], Artificial Bee Colony optimization (ABC), and Bacterial Foraging (BFA) algorithms, it is indeed much simpler both in concept and implementation. Due to its excellent performances, FA has been widely applied to many optimization fields, including optimization [3][4], data mining [5] and digital image processing [6] and so on.…”

Section: Introductionmentioning

confidence: 99%

A Novel and Improved Firefly Algorithm Based on Two-order Oscillation

Sui¹,

Yi²,

Yu³

2017

In this paper, the conventional firefly algorithm will be introduced and improved using two-order oscillation. And an improved firefly algorithm based on two-order oscillation is proposed. And this method will be deduced and analyzed for astringency. Six typical functions will be tested to prove performances. Global Max/Min values in six multimodal functions could be found accurately with proposed scheme. The experiment results show our proposed method has excellent performances than conventional one.

“…Natural phenomenon includes the Tabu search, simulated annealing, Gravitational force [5], Water drops, etc. Algorithms based on organisms' behaviors include Bacterial behavior, Ant behavior [6], Bee behavior, Bird behavior, Whale behavior, firefly behavior [7] and the recent Grey wolf behavior and monkey behavior.…”

Section: Swarm Intelligence Algorithmsmentioning

confidence: 99%

Monkey Behavior Based Algorithms - A Survey

Devi¹,

Sathya²

2017

Abstract-Swarm intelligence algorithms (SIA) are bioinspired techniques based on the intelligent behavior of various animals, birds, and insects. SIA are problemindependent and are efficient in solving real world complex optimization problems to arrive at the optimal solutions. Monkey behavior based algorithms are one among the SIAs first proposed in 2007. Since then, several variants such as Monkey search, Monkey algorithm, and Spider Monkey optimization algorithms have been proposed. These algorithms are based on the tree or mountain climbing and food searching behavior of monkeys either individually or in groups. They were designed with various representations, covering different behaviors of monkeys and hybridizing with the efficient operators and features of other SIAs and Genetic algorithm. They were explored for applications in several fields including bioinformatics, civil engineering, electrical engineering, networking, data mining etc. In this survey, we provide a comprehensive overview of monkey behavior based algorithms and their related literatures and discuss useful research directions to provide better insights for swarm intelligence researchers.