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Neural Computing and Applications

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04-07-2018 | S.I.: Emerging Intelligent Algorithms for Edge-of-Things Computing

A new binary salp swarm algorithm: development and application for optimization tasks

Authors: Rizk M. Rizk-Allah, Aboul Ella Hassanien, Mohamed Elhoseny, M. Gunasekaran

Published in: Neural Computing and Applications | Issue 5/2019

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Abstract

Salp swarm algorithm (SSA) is one of the recent meta-heuristic algorithms that imitate the behaviors of salps during the navigating and foraging in oceans to perform global optimization. However, the original study of this algorithm was proposed to solve continuous problems, and it cannot be applied to binary problems directly. In this paper, a new binary version of the SSA named BSSA is proposed based on a modified Arctan transformation. This modification has two features regarding the transfer function, namely multiplicity and mobility. By this modification, the exploration and exploitation capabilities can be enhanced. The proposed BSSA is compared among four variants of transfer functions for solving global optimization problems. Also, a comparative study with different binary algorithms including binary particle swarm, binary bat algorithm and binary sine–cosine algorithm on twenty-four benchmark problems is conducted. Furthermore, the nonparametric statistical test based on Wilcoxon’s rank-sum is carried out at 5% significance level to judge statistically the significant of the obtained results among the different algorithms. The results affirm the superior performance of the modified BSSA variant over the other variants as well as the existing approaches regarding solution quality.

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Prescilla K, Immanuel Selvakumar A (2013) Modified Binary Particle Swarm optimization algorithm application to real-time task assignment in heterogeneous multiprocessor. Microprocess Microsyst 37:583–589CrossRef

Korkmaz S, Babalik A, Servet KM (2017) An artificial algae algorithm for solving binary optimization problems. Int J Mach Learn Cybernet. https://doi.org/10.1007/s13042-017-0772-7

Beskirli M, Koc I, Hakli H, Kodaz H (2018) A new optimization algorithm for solving wind turbine placement problem: binary artificial algae algorithm. Renew Energy 121:301–308CrossRef

Rizk-Allah RM, Hassanien AE (2018) New binary bat algorithm for solving 0–1 knapsack problem. Complex Intell Syst 4:31–53CrossRef

Rizk-Allah RM (2014) A novel multi-ant colony optimization for multi-objective resource allocation problems. Int J Math Arch 5:183–192

Fan K, Weijia Y, Li Y (2013) An effective modified binary particle swarm optimization (mBPSO) algorithm for multi-objective resource allocation problem (MORAP). Appl Math Comput 221:257–267MathSciNetMATH

Pal A, Maiti J (2010) Development of a hybrid methodology for dimensionality reduction in Mahalanobis-Taguchi system using Mahalanobis distance and binary particle swarm optimization. Expert Syst Appl 37:1286–1293CrossRef

Babaoglu I, Findik O, Ulker E (2010) A comparison of feature selection models utilizing binary particle swarm optimization and genetic algorithm in determining coronary artery disease using support vector machine. Expert Syst Appl 37:3177–3183CrossRef

Qiao LY, Peng XY, Peng Y (2006) BPSO-SVM wrapper for feature subset selection. Dianzi Xuebao (Acta Electronica Sinica) 34:496–498

10.

Emary E, Zawbaa HM, Hassanien AE (2016) Binary grey wolf optimization approaches for feature selection. Neurocomputing 172:371–381CrossRef

11.

Beheshti Z, Shamsuddin SM, Hasan S (2015) Memetic binary particle swarm optimization for discrete optimization problems. Inf Sci 299:58–84CrossRef

12.

Krasimira G, Vassil G (2011) Linear integer programming methods and approaches—a survey. J Cybern Inf Technol 11:3–25MathSciNet

13.

Serigne G, Philippe M (2009) A linearization framework for unconstrained quadratic (0–1) problems. Discrete Appl Math 157:1255–1266MathSciNetCrossRefMATH

14.

Sherali HD, Driscoll PJ (2000) Evolution, and state-of-the-art in integer programming. J Comput Appl Math 124:319–340MathSciNetCrossRefMATH

15.

Yang XS (2008) Nature-inspired metaheuristic algorithms. Luniver Press, Cambridge

16.

Mirjalili S (2015) The ant lion optimizer. Adv Eng Softw 83:80–98CrossRef

17.

John MC (2005) Genetic algorithms for modelling and optimization. J Comput Appl Math 184:205–222MathSciNetCrossRefMATH

18.

Dorigo M, Birattari M, Stutzle T (2006) Ant colony optimization. Comput Intell Mag 1:28–39CrossRef

19.

Eberhart RC, Kennedy J (1995) A new optimizer using particle swarm theory. In: Proceedings of the sixth international symposium on micro machine and human science, pp 39–43

20.

Storn R, Price K (1997) Differential evolution-a simple and efficient heuristic for global optimization over continuous spaces. J Global Optim 11:341–359MathSciNetCrossRefMATH

21.

Karaboga D, Basturk B (2007) A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm. J Global Optim 39:459–471MathSciNetCrossRefMATH

22.

Yang XS, Deb S (2009) Cuckoo search via Lévy flights. In: World congress on nature & biologically inspired computing, 2009. NaBIC 2009, pp 210–214

23.

Rashedi E, Nezamabadi-Pour H, Saryazdi S (2009) GSA: a gravitational search algorithm. Inform Sci 179:2232–2248CrossRefMATH

24.

Kaveh A, Talatahari S (2010) A novel heuristic optimization method: charged system search. Acta Mech 213:267–289CrossRefMATH

25.

Yang XS (2010) Firefly algorithm, Lévy flights and global optimization. In: Bramer M, Ellis R, Petridis M (eds) Research and development in intelligent systems XXVI. Springer, London

26.

Seyedali M, Mohammad MS, Andrew L (2014) Grey wolf optimizer. Adv Eng Softw 69:46–61CrossRef

27.

Kaveh A, Ghazaan MI (2014) Enhanced colliding bodies optimization for design problems with continuous and discrete variables. Adv Eng Softw 77:66–75CrossRef

28.

Rizk-Allah RM, Hassanien AE, Bhattacharyya S (2018) Chaotic crow search algorithm for fractional optimization problems. Appl Soft Comput (in press)

29.

Rizk-Allah RM, Abdel Mageed HM, El-Sehiemy RA, Abdel Aleem SHE, El Shahat A (2017) A new sine cosine optimization algorithm for solving combined non-convex economic and emission power dispatch problems. Int J Energy Convers 5:180–192

30.

Rizk-Allah RM (2018) Hybridizing sine cosine algorithm with multi-orthogonal search strategy for engineering design problems. J Comput Des Eng 5:249–273

31.

Mousa AA, Abd El-Wahed WF, Rizk-Allah RM (2011) A hybrid ant colony optimization approach based local search scheme for multiobjective design optimizations. Electr Power Syst Res 81:1014–1023CrossRef

32.

Rizk-Allah RM, Zaki EM, El-Sawy AA (2013) Hybridizing ant colony optimization with firefly algorithm for unconstrained optimization problems. Appl Math Comput 224:473–483MathSciNetMATH

33.

El-Sawy AA, Zaki EM, Rizk-Allah RM (2013) A novel hybrid ant colony optimization and firefly algorithm for solving constrained engineering design problems. J Nat Sci Math 6:1–22

34.

El-Sawy AA, Zaki EM, Rizk-Allah RM (2013) A novel hybrid ant colony optimization and firefly algorithm for multi-objective optimization problems. Int J Math Arch 4:152–161MATH

35.

Rizk-Allah RM (2016) Hybridization of fruit fly optimization algorithm and firefly algorithm for solving nonlinear programming problems. Int J Swarm Intell Evol Comput 5:1–10

36.

Rizk-Allah RM, El-Sehiemy RA, Deb S, Wang G (2017) A novel fruit fly framework for multi-objective shape design of tubular linear synchronous motor. J Supercomput 73:1235–1256CrossRef

37.

Tharwat A, Elhoseny M, Hassanien AE, Gabel T, Arunkumar N (2018) Intelligent Beziér curve-based path planning model using chaotic particle swarm optimization algorithm. Clust Comput. https://doi.org/10.1007/s10586-018-2360-3

38.

Hassanien AE, Alamry E (2015) Swarm intelligence: principles, advances, and applications. CRC-Taylor & Francis Group, Boca Raton (CAT# K26721). ISBN 9781498741064CrossRef

39.

Mirjalili S, Faris H, Gandomi AH, Mirjalili SM, Mirjalili SZ, Saremi S (2017) Salp swarm algorithm: a bio-inspired optimizer for engineering design problems. Adv Eng Softw 114:163–191CrossRef

40.

Jiang F, Xia H, Tran QA, Ha QM, Tran NQ, Hu J (2017) A new binary hybrid particle swarm optimization with wavelet mutation. Knowl Based Syst 130:90–101CrossRef

41.

Liang JJ, Suganthan PN, Deb K (2005) Novel composition test functions for numerical global optimization. In: IEEE swarm intelligence symposium, pp 68–75

42.

Derrac J, García S, Molina D, Herrera F (2011) A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms. Swarm Evol Comput 1:3–18CrossRef

43.

Tharwat A, Mahdi H, Elhoseny M, Hassanien AE (2018) Recognizing human activity in mobile crowdsensing environment using optimized k-NN algorithm. Expert Syst Appl. https://doi.org/10.1016/j.eswa.2018.04.017

44.

Hosseinabadi AAR, Vahidi J, Saemi B, Sangaiah AK, Elhoseny M (2018) Extended Genetic Algorithm for solving open-shop scheduling problem. Soft Comput. https://doi.org/10.1007/s00500-018-3177-y

45.

Abdelaziza A, Elhoseny M, Salama AS, Riad AM (2018) A machine learning model for improving healthcare services on cloud computing environment. Measurement 119:117–128. https://doi.org/10.1016/j.measurement.2018.01.022 CrossRef

46.

Abd El Aziz M, Hemdan AM, Ewees AA, Elhoseny M, Shehab A, Hassanien AE, Xiong S (2017), Prediction of biochar yield using adaptive neuro-fuzzy inference system with particle swarm optimization. In: 2017 IEEE PES PowerAfrica conference, June 27–30, Accra-Ghana, IEEE, 2017, pp 115–120. https://doi.org/10.1109/powerafrica.2017.7991209

47.

Ewees AA, Abd El Aziz M, Elhoseny M (2017) Social-spider optimization algorithm for improving ANFIS to predict biochar yield. In: 8th International conference on computing, communication and networking technologies (8ICCCNT), July 3–5, Delhi-India, IEEE, 2017

48.

Elhoseny M, Tharwat A, Yuan X, Hassanien AE (2018) Optimizing K-coverage of mobile WSNs. Expert Syst Appl 92:142–153. https://doi.org/10.1016/j.eswa.2017.09.008 CrossRef

49.

Elhoseny M, Abdelaziz A, Salama A, Riad AM, Sangaiah AK, Muhammad K (2018, in press) A hybrid model of internet of things and cloud computing to manage big data in health services applications. Future Gen Comput Syst

50.

Sarvaghad-Moghaddam M, Orouji AA, Ramezani Z, Elhoseny M, Farouk A, Arun kumar N (2018) Modelling the Spice parameters of SOI MOSFET using a combinational algorithm. Clust Comput. https://doi.org/10.1007/s10586-018-2289-6

51.

Rizk-Allah RM, Hassanien AE, Elhoseny M (2018) A multi-objective transportation model under neutrosophic environment. Comput Electr Eng. https://doi.org/10.1016/j.compeleceng.2018.02.024

52.

Batle J, Naseri M, Ghoranneviss M, Farouk A, Alkhambashi M, Elhoseny M (2017) Shareability of correlations in multiqubit states: optimization of nonlocal monogamy inequalities. Phys Rev A 95(3):032123. https://doi.org/10.1103/PhysRevA.95.032123 CrossRef

53.

Elhoseny M, Tharwat A, Farouk A, Hassanien AE (2017) K-coverage model based on genetic algorithm to extend WSN lifetime. IEEE Sens Lett 1(4):1–4. https://doi.org/10.1109/lsens.2017.2724846 CrossRef

54.

Yuan X, Elhoseny M, El-Minir HK, Riad AM (2017) A genetic algorithm-based, dynamic clustering method towards improved WSN longevity. J Netw Syst Manag 25(1):21–46. https://doi.org/10.1007/s10922-016-9379-7 CrossRef

55.

Elhoseny M, Shehab A, Yuan X (2017) Optimizing robot path in dynamic environments using genetic algorithm and bezier curve. J Intell Fuzzy Syst 33(4):2305–2316. https://doi.org/10.3233/jifs-17348 CrossRefMATH

56.

Elhoseny M, Tharwat A, Hassanien AE (2017) Bezier curve based path planning in a dynamic field using modified genetic algorithm. J Comput Sci. https://doi.org/10.1016/j.jocs.2017.08.004

57.

Metawaa N, Hassana MK, Elhoseny M (2017) Genetic algorithm based model for optimizing bank lending decisions. Expert Syst Appl 80:75–82. https://doi.org/10.1016/j.eswa.2017.03.021 CrossRef

58.

Metawa N, Elhoseny M, Hassan MK, Hassanien AE (2016) Loan portfolio optimization using Genetic Algorithm: a case of credit constraints. In: Proceedings of 12th international computer engineering conference (ICENCO). IEEE, pp 59–64. https://doi.org/10.1109/icenco.2016.7856446

Title: A new binary salp swarm algorithm: development and application for optimization tasks
Authors: Rizk M. Rizk-Allah
Aboul Ella Hassanien
Mohamed Elhoseny
M. Gunasekaran
Publication date: 04-07-2018
Publisher: Springer London
Published in: Neural Computing and Applications / Issue 5/2019
Print ISSN: 0941-0643
Electronic ISSN: 1433-3058
DOI: https://doi.org/10.1007/s00521-018-3613-z

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