Improved Cuckoo Search algorithm for numerical function optimization

Li, Jianjun; Zeng, Min; Ge, Yifan; Wu, Changzhi; Wang, Xiangyu

doi:10.3934/jimo.2018142

Cited by 4 publications

(5 citation statements)

References 24 publications

(36 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…where pa (r) ∈[0.15,0.55]; pa (r)min represents the minimum values of pa (r) ; pa (r)max represents the maximum values of pa (r) ; rand () is a random number generated uniformly distributed between (0,1); τ (a, b) is a gamma-distributed random number obeying shape parameter a and scale parameter b; and λ is used to control the deviation between the inertia weight and the expected value [37]. ( 23)…”

Section: Algorithm Flowmentioning

confidence: 99%

The Optimization of Split Demand Route Planning Under Metro-Truck Collaborative Distribution

Li,

Wang,

Liu

2024

Urban Rail Transit

View full text Add to dashboard Cite

With the evolution of people's consumption habits and the rapid growth of urban logistics, the number of trucks and delivery frequency has increased significantly, exacerbating urban traffic congestion and environmental pollution. Consequently, there is an urgent need to improve the current inefficient and highly polluted distribution mode. Currently, in most cities in China, the metro passenger flow is insufficient, and the capacity is excessive during off-peak hours, resulting in underutilized carriage capacity. The integration of surface and underground transport resources can effectively address these issues and facilitate complementary advantages and win–win cooperation between express companies and metro enterprises. This study proposes an innovative problem of split demand route planning in the cooperative distribution system involving express companies and subways. A cooperative distribution model is developed to minimize the total cost, and solved by the Cuckoo Search algorithm to obtain the optimized solution. The model is applied to the urban rail transit network in Changchun, and the results demonstrate that it is effective in reducing truck mileage and distribution costs. Compared to the single delivery pattern by trucks, the cooperative distribution approach proves to be more cost-effective and environmentally friendly.

show abstract

Section: Algorithm Flowmentioning

confidence: 99%

The Optimization of Split Demand Route Planning Under Metro-Truck Collaborative Distribution

Li,

Wang,

Liu

2024

Urban Rail Transit

View full text Add to dashboard Cite

show abstract

“…A cuckoo spawns in another birds' nest [18]. If the nest owner finds these exotic birds' eggs, they will abandon their young or look for a new nest [19].…”

Section: The Standard Cuckoo Search Algorithm (Cs)mentioning

confidence: 99%

An Improved Cuckoo Search Algorithm Based on Elite Opposition-based Learning for Indoor Visible Light Positioning

Yang Yang,

Mao-Sheng Fu

et al. 2023

Journal of Computers

View full text Add to dashboard Cite

In the cuckoo search algorithm, the structure is simple, and the parameters are not much, but it is easy to trap into the local optimum, and in the later period, the convergence speed is plodding. Aiming at the shortcomings of the standard cuckoo algorithm, a modified cuckoo algorithm (EACSDAM) is presented in this paper, which adopts elite reverse learning to enhance the population diversity, and increases the step factor and discovery probability to improve the global detection and local searchability. Eight standard test functions are used to simulate the EACSDAM algorithm. Compared with the standard cuckoo algorithm and the other two improved algorithms, the accuracy and convergence speed of EACSDAM are greatly improved. In the end, EACSDAM is used to optimize the indoor 3D visible light positioning. The simulation results indicate that EACSDAM has a more powerful ability for global optimization, and more accurate positioning, and the positioning error is significantly reduced.

show abstract

“…Entomologists have found that gulfs raise their young ones by depositing in other birds' nests rather than building their nests [28]. However, these exotic birds' eggs may be discovered by the host, which may abandon the young birds or rebuild the new nest [29].…”

Section: The Standard Cs Algorithmmentioning

confidence: 99%

“…The standard CS algorithm uses levy flight random walk and preference random walk strategies to update the nest locations. However, due to the uncertainty of the random walk, the search capability gets weaker, and the convergence speed also slows down [28]. In ISCS, a nonlinear decreasing inertia weight and the adaptive scaling factor are proposed to enhance convergence speed and solution accuracy.…”

Section: The Iscs Algorithmmentioning

confidence: 99%

An Improved Cuckoo Search Algorithm Based on Inertial Weight and Scaling Factor

楊恙¹,

Yang²,

Fu³

et al. 2022

Journal of Compurters

View full text Add to dashboard Cite

This paper presents a novel and an improved cuckoo search algorithm (ISCS), different from other techniques, which sets nonlinear decreasing inertia weight and adaptive scaling factor. As the iteration goes on, these two parameters are controlled by two functions to change the iterations dynamically. At the beginning of the iteration, the values of the two parameters are favorable for global search, and at the end of the iteration, their values are more favorable for local optimization. In this work, 23 classical benchmark functions are selected to improve the accuracy and convergence speed by conducting the simulation experiments on CS, ISCS and other three algorithms. The results show that the improved cuckoo algorithm enhances the accuracy of understanding and speeds up the convergence of the curves. Finally, ISCS is applied to probabilistic neural network (PPN) neural network classification and recognition technology, and the results show that the optimization of ISCS can effectively improve the classification accuracy of the test sets, and has diverse applications.

show abstract

Improved Cuckoo Search algorithm for numerical function optimization

Cited by 4 publications

References 24 publications

The Optimization of Split Demand Route Planning Under Metro-Truck Collaborative Distribution

The Optimization of Split Demand Route Planning Under Metro-Truck Collaborative Distribution

An Improved Cuckoo Search Algorithm Based on Elite Opposition-based Learning for Indoor Visible Light Positioning

An Improved Cuckoo Search Algorithm Based on Inertial Weight and Scaling Factor

Contact Info

Product

Resources

About