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Duck swarm algorithm: a novel swarm intelligence algorithm [article]

Mengjian Zhang, Guihua Wen, Jing Yang
2021 arXiv   pre-print
This algorithm is inspired by the searching for food sources and foraging behaviors of the duck swarm.  ...  Overall, the comparison results revealed that the DSA is a promising and very competitive algorithm for solving different optimization problems.  ...  Qin A K, Huang V L, Suganthan P N (2009) Differential evolution algorithm with strategy adaptation for global numerical optimization.  ... 
arXiv:2112.13508v1 fatcat:skzrstg6hfbobaq7y34g3eprzq

Chaotic Election Algorithm

Hojjat Emami
2019 Computing and informatics  
The election algorithm is a socio-politically inspired strategy that mimics the behavior of candidates and voters in presidential election process.  ...  A novel Chaotic Election Algorithm (CEA) is presented for numerical function optimization. CEA is a powerful enhancement of election algorithm.  ...  Differential Evolution (SaDE) algorithm [61] , adaptive Differential Evolution (JDE) algorithm [62] , PSO2011 [50] , Election algorithm Emami2015, Socio Evolution & Learning Optimization (SELO) algorithm  ... 
doi:10.31577/cai_2019_6_1444 fatcat:zkghu753x5g7jijbrtud3jfccy

Opposition based Chaotic Differential Evolution algorithm for solving global optimization problems

Radha Thangaraj, Millie Pant, Thanga Raj Chelliah, Ajith Abraham
2012 2012 Fourth World Congress on Nature and Biologically Inspired Computing (NaBIC)  
A modified differential evolution (DE) algorithm based on opposition based learning and chaotic sequence named Opposition based Chaotic Differential Evolution (OCDE) is proposed.  ...  The proposed OCDE algorithm is different from basic DE in two aspects.  ...  and Biologically Inspired Computing (NaBIC) Fourth World Congress on Nature and Biologically Inspired Computing (NaBIC) Fourth World Congress on Nature and Biologically Inspired Computing (NaBIC  ... 
doi:10.1109/nabic.2012.6402168 dblp:conf/nabic/ThangarajPCA12 fatcat:zsmexoff5nawnjyzkptm7twtpe

Memetic Search in Differential Evolution Algorithm

Sandeep Kumar, Vivek Kumar Sharma, Rajani Kumari
2014 International Journal of Computer Applications  
The position update equation is inspired from the memetic search in artificial bee colony algorithm. The proposed strategy is named as Memetic Search in Differential Evolution (MSDE).  ...  Differential Evolution (DE) is a renowned optimization stratagem that can easily solve nonlinear and comprehensive problems.  ...  The paper also includes a concise appraisal of well-organized and newly developed nature-inspired algorithm, that is to say Differential Evolution.  ... 
doi:10.5120/15582-4406 fatcat:oiafxupetjchnjinzlifabyzq4

Agent State Flipping Based Hybridization of Heuristic Optimization Algorithms: A Case of Bat Algorithm and Krill Herd Hybrid Algorithm

Robertas Damaševičius, Rytis Maskeliūnas
2021 Algorithms  
The experimental results demonstrate that the hybrid scheme outperformed the baseline algorithms (mean rank for the hybrid BA-KH algorithm is 1.279 vs. 1.958 for KH and 2.763 for BA).  ...  An evaluation using two bio-inspired algorithms (bat algorithm (BA) and krill herd (KH)) and 12 optimization problems (cross-in-tray, rotated hyper-ellipsoid (RHE), sphere, sum of squares, sum of different  ...  The algorithms used for comparison are as follows: dingo optimization algorithm (DOA), mine blast algorithm (MBA), salp swarm algorithm (SSA), PSO with differential evolution (PSO-DE), and DE with dynamic  ... 
doi:10.3390/a14120358 fatcat:gjnxjvjxq5huhefx7krqjzxbay

A Novel Routing Technique for Congestion Avoidance in WSN using Bat Algorithm

Aditya Prakash, Noorinder Kaur
2018 International Journal of Computer Applications  
Nature inspired optimization algorithms are useful for solving different kind of engineering problems, combinatorial problems and many more.  ...  Bat Algorithm is one of the nature inspired techniques which fulfill the criteria of finding the optimized and better result, in solving most of the problems.  ...  However, the cost reflecting is minimal, as the optimal path is traced by nature inspired algorithm. Comparison shows the better result of proposed algorithm.  ... 
doi:10.5120/ijca2018916847 fatcat:rdjmtyx2krcuxoxqnhzlfcmlku

Hierarchical Collaborated Fireworks Algorithm

Yifeng Li, Ying Tan
2022 Electronics  
Experimental results validate that the hierarchical collaborated fireworks algorithm outperforms former fireworks algorithms significantly and achieves similar results compared with state-of-the-art evolutionary  ...  algorithms.  ...  The population topology mechanism has also been naturally applied to differential evolution [26] and genetic algorithm [27] . Dynamic topologies are common in recent EAs and SIOAs.  ... 
doi:10.3390/electronics11060948 fatcat:tozchptd25fctdi5a7nebtso24

Germinal Center Optimization Algorithm

Carlos Villaseñor, Nancy Arana-Daniel, Alma Y. Alanis, Carlos López-Franco, Esteban A. Hernandez-Vargas
2018 International Journal of Computational Intelligence Systems  
To show the performance, we include a benchmark with the comparison of our approach versus some of the state-of-the-art bio-inspired optimization algorithms.  ...  We also propose the combination of this selection method with the use of one Differential Evolution-based strategy to substitute the somatic hypermutation process.  ...  Differential Evolution Differential Evolution 15 (DE) is a successful optimization algorithm for multivariate functions. DE is a population-based metaheuristic.  ... 
doi:10.2991/ijcis.2018.25905179 fatcat:shnl3lhigvcmvnvjlz3o23ecf4

Improving Monarch Butterfly Optimization Algorithm with Self-Adaptive Population

Hui Hu, Zhaoquan Cai, Song Hu, Yingxue Cai, Jia Chen, Sibo Huang
2018 Algorithms  
Inspired by the migration behavior of monarch butterflies in nature, Wang et al. proposed a novel, promising, intelligent swarm-based algorithm, monarch butterfly optimization (MBO), for tackling global  ...  This also implies the self-adaptive strategy is an effective way to improve the performance of the basic MBO algorithm.  ...  [91] suggested a synergy of fuzzy logic and nature-inspired algorithms in the context of the nature-inspired optimal tuning of the input membership functions of a class of Takagi-Sugeno-Kang (TSK) fuzzy  ... 
doi:10.3390/a11050071 fatcat:rbpxuidxuze6xiops4jby6bxqy

Flower Pollination Algorithm for Multimodal Optimization

Jorge Gálvez, Erik Cuevas, Omar Avalos
2017 International Journal of Computational Intelligence Systems  
Under MFPA, the original Flower Pollination Algorithm (FPA) is enhanced with multimodal capabilities in order to find all possible optima in an optimization problem.  ...  This paper proposes a new algorithm called Multimodal Flower Pollination Algorithm (MFPA).  ...  The experiments compare the performance of MFPA against the Fitness Sharing Differential Evolution (FSDE), the Crowding Differential Evolution (CDE), the Clonal Selection Algorithm (CSA), the Deterministic  ... 
doi:10.2991/ijcis.2017.10.1.42 fatcat:yoiok5yrurfmlkq6ec36gz5vv4

Covariance Matrix Learning Differential Evolution Algorithm Based on Correlation

Sainan Yuan, Quanxi Feng
2021 International Journal of Intelligence Science  
The experimental results show that the algorithm proposed in this paper is an effective algorithm.  ...  Finally, the algorithm is tested on the CEC2005, and the experimental results are compared with other effective differential evolution algorithms.  ...  This work is proudly supported in part by National Natural Science Foundation of China (No. 61763008, 11661030, 11401357, Conflicts of Interest The authors declare no conflicts of interest regarding  ... 
doi:10.4236/ijis.2021.111002 fatcat:nm7wjwnu55gbdnhiuuaczquplq

Comprehensive Taxonomies of Nature- and Bio-inspired Optimization: Inspiration versus Algorithmic Behavior, Critical Analysis and Recommendations [article]

Daniel Molina and Javier Poyatos and Javier Del Ser and Salvador García and Amir Hussain and Francisco Herrera
2020 arXiv   pre-print
From our analysis we conclude that a poor relationship is often found between the natural inspiration of an algorithm and its behavior.  ...  In recent years, a great variety of nature- and bio-inspired algorithms has been reported in the literature.  ...  It can be observed that in most nature-and bio-inspired algorithms, new solutions are generated by differential vector movement over existing ones (64% vs 36%).  ... 
arXiv:2002.08136v2 fatcat:paeupscdt5hgzjtqzdtpcuucfq

A New Differential Mutation Based Adaptive Harmony Search Algorithm for Global Optimization

Xinchao Zhao, Rui Li, Junling Hao, Zhaohua Liu, Jianmei Yuan
2020 Applied Sciences  
Experimental comparison among well-known HS variants and several state-of-the-art evolutionary algorithms on CEC 2014 benchmark indicates that the aHSDE has a very competitive performance.  ...  In order to make full use of harmony memory to generate new solutions, this paper proposes a new adaptive harmony search algorithm (aHSDE) with a differential mutation, periodic learning and linear population  ...  Experimental Comparison with HS Variants and Well-Known EAs aHSDE vs.  ... 
doi:10.3390/app10082916 fatcat:o2lgqmar6bb5hmegtipup42s4m

Buyer Inspired Meta-Heuristic Optimization Algorithm

Sanjoy Debnath, Wasim Arif, Srimanta Baishya
2020 Open Computer Science  
AbstractNature inspired swarm based meta-heuristic optimization technique is getting considerable attention and established to be very competitive with evolution based and physical based algorithms.  ...  This paper proposes a novel Buyer Inspired Meta-heuristic optimization Algorithm (BIMA) inspired form the social behaviour of human being in searching and bargaining for products.  ...  In an evolutionary algorithm, Differential Evolution (DE) [27] is mostly preferred for solving problems with real valued parameters and since finding an optimal hyperplane is a hard computing task, this  ... 
doi:10.1515/comp-2020-0101 fatcat:tiqcbjjzcrfg3mi533q6kvkrau

Investigating the parameter space of evolutionary algorithms

Moshe Sipper, Weixuan Fu, Karuna Ahuja, Jason H. Moore
2018 BioData Mining  
Through an extensive series of experiments over multiple evolutionary algorithm implementations and problems we show that parameter space tends to be rife with viable parameters, at least for 25 the problems  ...  The practice of evolutionary algorithms involves the tuning of many parameters. How big should the population be? How many generations should the algorithm run?  ...  [8] , mentioned above, described an efficient technique for adapting control parameter settings associated with differential evolution (DE).  ... 
doi:10.1186/s13040-018-0164-x pmid:29467825 pmcid:PMC5816380 fatcat:4isbh6l47zaafmk5salg33blyy
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