Abstract
As a new nature-inspired swarm intelligence optimizer, squirrel search algorithm (SSA) has shown potential to solve several real-world problems, but for some complex problems, it still suffers from degraded performance. In this paper, a hybrid squirrel search algorithm (NOSSA) combined with optimal neighborhood update and quasi-opposition learning strategies is proposed to overcome the drawback of population update guided only by leading individuals in SSA. NOSSA adopts a stochastic optimal neighborhood update strategy to improve convergence speed and accuracy, and incorporates a Quasi-opposition learning strategy to enhance exploration. To verify its efficiency, NOSSA has been tested on 23 classic benchmark functions. Experimental results show that NOSSA has better performance on search-efficiency, convergence rate and solution accuracy compared with the representative stochastic optimizers. Furthermore, intelligent algorithms are introduced into the optimal multi-degree reduction of Ball Bézier curves and two new methods are proposed for the multi-degree reduction of center curve and radius function of Ball Bézier curve respectively. Experimental results demonstrate the effectiveness of the methods and show that NOSSA performs best among the representative stochastic optimizers in the degree reduction. The methods achieve the automatic and intelligent degree reduction of Ball Bézier curves.











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References
Holland JH (1975) Adaptation in natural and artificial systems. University of Michigan Press, Ann Arbor
Robinson J, Rahmat-Samii Y (2004) Particle swarm optimization in electromagnetic. IEEE Trans Antennas Propag 52:397–407
Mirjalili S, Mirjalili SM, Lewis A (2014) Grey wolf optimizer. Adv Eng Softw 69:46–61
Mirjalili S (2015) Moth-flame optimization algorithm: a novel nature-inspired heuristic paradigm. Knowl-Based Syst 89:228–249
Mirjalili S, Lewis A (2016) The whale optimization algorithm. Adv Eng Softw 95:51–67
Mirjalili S, Gandomi AH, Mirjalili SZ, Saremi S, Faris H, Mirjalili SM (2017) Salp swarm algorithm: a bio-inspired optimizer for engineering design problems. Adv Eng Softw 114:163–191
Heidari AA, Mirjalili S, Faris H, Aljarah I, Mafarja M, Chen H (2019) Harris hawks optimization: algorithm and applications. Future Gener Comput Syst 97:849–872
Mirjalili S (2016) A sine cosine algorithm for solving optimization problems. Knowl-Based Syst 96:120–133
Jain M, Singh V, Rani A (2019) A novel nature-inspired algorithm for optimization: squirrel search algorithm. Swarm Evol Comput 44:148C175
Tanweer MR, Suresh S, Sundararajan N (2015) Self regulating particle swarm optimization algorithm. Inf Sci 294:182–202
Lenin K (2020) Real power loss reduction by Duponchelia fovealis optimization and enriched squirrel search optimization algorithms. Soft Comput 24(23):17863–17873
Deb D, Roy S (2020) Brain tumor detection based on hybrid deep neural network in MRI by adaptive squirrel search optimization. Ultimed Tools Appl 80:2621–2645
Wolpert DH, Macready WG (1997) No free lunch theorems for optimization. IEEE Trans Evol Comput 1(1):67–82
Guo W, Wang Y, Dai F, Xu P (2020) Improved sine cosine algorithm combined with optimal neighborhood and quadratic interpolation strategy. Eng Appl Artif Intell 94:103779
Mehrabian AR, Lucas C (2006) A novel numerical optimization algorithm inspired from weed colonization. Ecol Inf 1:355–366
Hu H, Zhang L, Bai Y, Wang P, Tan X (2019) A hybrid algorithm based on squirrel search algorithm and invasive weed optimization for optimization. IEEE Access 7:105652–105668
Gupta S, Deep K (2020) A memory-based grey wolf optimizer for global optimization tasks. Appl Soft Comput 93:106367
Kohli M, Arora S (2018) Chaotic grey wolf optimization algorithm for constrained optimization problems. J Comput Des Eng 5(4):458–472
Saxena MA, Kumar R, Das S (2019) \(\beta \)-chaotic map enabled grey wolf optimizer. Appl Soft Comput 75:84–105
Tang Y, Wang Z, Fang J (2011) Feedback learning particle swarm optimization. Appl Soft Comput 11:4713–4725
Lin CJ, Chern MS, Chih M (2016) A binary particle swarm optimization based on the surrogate information with proportional acceleration coefficients for the 0–1 multidimensional knapsack problem. J Ind Prod Eng 33:77–102
Ardizzon G, Cavazzini G, Pavesi G (2015) Adaptive acceleration coefficients for a new search diversification strategy in particle swarm optimization algorithms. Inf Sci 299:337–378
Gülcü Ş, Kodaz H (2015) A novel parallel multi-swarm algorithm based on comprehensive learning particle swarm optimization. Eng Appl Artif Intell 45:33–45
Wang F, Zhang H, Li K et al (2018) A hybrid particle swarm optimization algorithm using adaptive learning strategy. Inf Sci 436:162–177
Ouyang HB, Gao LQ, Li S et al (2017) Improved global-best-guided particle swarm optimization with learning operation for global optimization problems. Appl Soft Comput 52:987–1008
Chen K, Zhou F, Yin L et al (2017) A hybrid particle swarm optimizer with sine cosine acceleration coefficients. Inf Sci 422:218–241
Tizhoosh HR (2005) Opposition-based learning: a new scheme for machine intelligence, In: International Conference on computational intelligence for modelling, control and automation International Conference on intelligent agents, web technologies and internet commerce (CIMCA-IAWTIC’06). IEEE 01:695–701
Guha D, Roy PK, Banerjee S (2016) Load frequency control of large scale power system using quasi-oppositional grey wolf optimization algorithm. Eng Sci Technol 19(4):1693–1713
Basu M (2016) Quasi-oppositional group search optimization for hydrothermal power system. Int J Electr Power Energy Syst 81:324–335
Nandi M, Shiva CK, Mukherjee V (2017) TCSC based automatic generation control of deregulated power system using quasi-oppositional harmony search algorithm. Eng Sci Technol 20(4):1380–1395
Ammad M, Misro M, Abbas M et al (2021) Generalized developable cubic trigonometric Bézier surfaces. Mathematics 9(3):283. https://doi.org/10.3390/math9030283
Majeed A, Abbas M, Qayyum F et al (2020) Geometric modeling using new cubic trigonometric B-Spline functions with shape parameter. Mathematics 8(12):2102. https://doi.org/10.3390/math8122102
Bashir U, Abbas M, Ali J (2013) The \(G^{2}\) and \(C^{2}\) rational quadratic trigonometric Bézier curve with two shape parameters with applications. Appl Math Comput 219(20):10183–10197
Usman M, Abbas M, Miura K (2020) Some engineering applications of new trigonometric cubic Bézier-like curves to free-form complex curve modeling. J Adv Mech Des Syst 14(4):JAMDSM0048
Bibi S, Abbas M, Miura K et al (2020) Geometric modeling of novel generalized hybrid trigonometric Bézier-like curve with shape parameters and its applications. Mathematics 8(6):967. https://doi.org/10.3390/math8060967
Majeed A, Abbas M, Miura K et al (2020) Surface modeling from 2D contours with an application to craniofacial fracture construction. Mathematics 8(8):1246. https://doi.org/10.3390/math8081246
Maqsood S, Abbas M, Miura K et al (2020) Geometric modeling and applications of generalized blended trigonometric Bézier curves with shape parameters. Adv Differ Equ 550:1–8
Leng C, Wu Z, Zhou M (2011) Reconstruction of tubular object with ball b-spline curve. In: Proceedings of computer graphics international
Wang X, Wu Z, Shen J et al (2016) Repairing the cerebral vascular through blending Ball B-Spline curves with \(G^{2}\) continuity. Neurocomputing 173:768–777
Xu X, Leng C, Wu Z (2011) Rapid 3d human modeling and animation based on sketch and motion database, In. Workshop on Digital Media and Digital Content Management (DMDCM) 2011, pp 121–124
Wu Z, Zhou M, Wang X et al (2007) An interactive system of modeling 3D trees with ball b-spline curves, In: 2007 10th IEEE International Conference on computer-aided design and computer graphics, 1:259–265
Zhu T, Tian F, Zhou Y et al (2008) Plant modeling based on 3D reconstruction and its application in digital museum. Int J Virt Real 7(1):81–88
Wu Z, Seah H, Zhou M (2007) Skeleton based parametric solid models: Ball B-Spline curves, In: 2007 10th IEEE International Conference on computer-aided design and computer graphics, pp 421–424
Fu Q, Wu Z, Zhou M, Zheng J, Wang X, Wang X et al (2018) An algorithm for finding intersection between ball B-spline curves. J Comput Appl Math 327:260–273
Liu X, Wang X, Wu Z, Zhang D, Liu X (2020) Extending Ball B-spline by B-spline. Comput Aided Geom Des 82:101926
Chen F, Lou W (2000) Degree reduction of interval Bézier curves. Comput Aided Des 32(6):571–582
Chen F, Yang W (2004) Degree reduction of disk Bézier curves. Comput Aided Geom Des 21(3):263–280
Shi M (2015) Degree reduction of classic disk rational Bézier curves in L2 norm, In: 2016 14th International Conference on computer-aided design and computer graphics, CAD/Graphics. 7450417, pp 202–203
Yang X-S (2010) Firefly algorithm, Lévy flights and global optimization. Springer, London, pp 209–218
Jensi R, Jiji GW (2016) An enhanced particle swarm optimization with Lévy flight for global optimization. Appl Soft Comput 43:248–261
Wu J, Zhang X (2015) Integro quadratic spline interpolation. Appl Math Model 39:2973–2980
Yao X, Liu Y, Lin G (1999) Evolutionary programming made faster. IEEE Trans Evol Comput 3(2):82–102
Digalakis J, Margaritis K (2001) On benchmarking functions for genetic algorithm. Int J Comput Math 77(4):481–506
Mirjalili S, Lewis A (2013) S-shaped versus V-shaped transfer functions for binary particle swarm optimization. Swarm Evol Comput 9:1–14
Mirjalili S, Mirjalili SM, Yang XS (2014) Binary bat algorithm. Neural Comput Appl 25(3–4):663–681
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This work is supported by the National Natural Science Foundation of China (Grant No. 51875454).
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Cao, H., Zheng, H. & Hu, G. The optimal multi-degree reduction of Ball Bézier curves using an improved squirrel search algorithm. Engineering with Computers 39, 1143–1166 (2023). https://doi.org/10.1007/s00366-021-01499-0
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DOI: https://doi.org/10.1007/s00366-021-01499-0
Keywords
- Squirrel search algorithm
- Optimal neighborhood
- Quasi-opposition learning
- Ball Bézier curve
- Multi-degree reduction