Complex-valued encoding symbiotic organisms search algorithm for global optimization

Miao, Fahui; Zhou, Yongquan; Luo, Qifang

doi:10.1007/s10115-018-1158-1

Cited by 23 publications

(5 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To corroborate the practicability and availability, the EAOA is used to resolve the project optimization problems, such as the welded beam project [31], tension/compression spring project [32], pressure vessel project [33], cantilever beam project [34], and speed reducer project [35].…”

Section: Eaoa For Solving Project Optimizationmentioning

confidence: 99%

A Novel Enhanced Arithmetic Optimization Algorithm for Global Optimization

Zhang

Huang

et al. 2022

IEEE Access

View full text Add to dashboard Cite

The arithmetic optimization algorithm (AOA) is based on the distribution character of the dominant arithmetic operators and imitates addition (A), subtraction (S), multiplication (M) and division (D) to find the global optimal solution in the entire search space. However, the basic AOA has some drawbacks of premature convergence, easily falls into a local optimal value, slow convergence rate, and low calculation precision. To improve the overall optimization ability and overcome the drawbacks of the basic AOA, an enhanced AOA (EAOA) based on the Lé vy variation and the differential sorting variation is proposed to solve the function optimization and the project optimization. The Lé vy variation increases population diversity, broadens the optimization space, enhances the global search ability and improves the calculation precision. The differential sorting variation filters out the optimal search agent, avoids search stagnation, enhances the local search ability and accelerates the convergence rate. The EAOA realizes complementary advantages of the Lé vy variation and the differential sorting variation to avoid falling into the local optimum and the premature convergence. The sixteen benchmark functions and five engineering design projects are applied to verify the effectiveness and feasibility of the EAOA. The EAOA is compared with other algorithms by minimizing the fitness value, such as artificial bee colony, ant line optimizer, cuckoo search, dragonfly algorithm, moth-flame optimization, sine cosine algorithm, water wave optimization and arithmetic optimization algorithm. The experimental results show that the overall optimization ability of the EAOA is superior to that of other algorithms, the EAOA can effectively balance the exploration and the exploitation to obtain the best solution. In addition, the EAOA has a faster convergence rate, higher calculation precision and stronger stability.

show abstract

Section: Eaoa For Solving Project Optimizationmentioning

confidence: 99%

A Novel Enhanced Arithmetic Optimization Algorithm for Global Optimization

Zhang

Huang

et al. 2022

IEEE Access

View full text Add to dashboard Cite

show abstract

“…Formula (31) uses a linear decreasing method, and the search range boundary is gradually reduced from 1 to 0.5 as the number of iterations increases. Therefore, the improved mathematical model for the generation of new individuals in the commensalism phase can be expressed as (32) According to the characteristics of the SOS algorithm parameters, this paper changes the uncontrollable random parameter into a controllable random parameter, so that the selection and change of the random parameter can be adapted to the development of the individual. This paper has made corresponding adjustments to some defects of the algorithm, and it is still the same as the original algorithm.…”

Section: Selection Of Random Numbers In Commensalism Phasementioning

confidence: 99%

“…The search range is extended from one dimension to flat, which improves the ability to find the global optimal value. 32 In addition, The SOS algorithm is also commonly used in route planning to find the optimal route. 33 In the optimization of power systems, a symbiosis search algorithm was used in 34 to solve economic scheduling problems that consider valve-point effects, restricted areas, transmission linepenalty, various bunkers, and other operating restrictions of distribution power systems.…”

Section: Introductionmentioning

confidence: 99%

Improved Symbiotic Organisms Search Algorithm for Optimal Operation of Active Distribution Systems Incorporating Renewables and Emerging Data‐Center Resources

Zeng

Hao

Wang

et al. 2021

Energy Science & Engineering

View full text Add to dashboard Cite

show abstract

“…e complex-valued encoding-driven optimization optimized the 0-1 knapsack problem [26]. e complex-valued encoding symbiotic organism search algorithm was proposed for the overall optimization [27]. e complex-valued encoding flower pollination algorithm optimized the constrained engineering optimization problems [28].…”

Section: Introductionmentioning

confidence: 99%

A Complex-Valued Encoding Multichain Seeker Optimization Algorithm for Engineering Problems

Duan

Luo

Liu

2022

Scientific Programming

View full text Add to dashboard Cite

This article comes up with a complex-valued encoding multichain seeker optimization algorithm (CMSOA) for the engineering optimization problems. The complex-valued encoding strategy and the multichain strategy are leaded in the seeker optimization algorithm (SOA). These strategies enhance the individuals’ diversity, enhance the local search, avert falling into the local optimum, and are the influential global optimization strategies. This article chooses fifteen benchmark functions, four proportional integral derivative (PID) control parameter models, and six constrained engineering problems to test. According to the experimental results, the CMSOA can be used in the benchmark functions, in the PID control parameter optimization, and in the optimization of constrained engineering problems. Compared to the particle swarm optimization (PSO), simulated annealing based on genetic algorithm (SA_GA), gravitational search algorithm (GSA), sine cosine algorithm (SCA), multiverse optimizer (MVO), and seeker optimization algorithm (SOA), the optimization ability and robustness of the CMSOA are better than those of others algorithms.

show abstract

Complex-valued encoding symbiotic organisms search algorithm for global optimization

Cited by 23 publications

References 26 publications

A Novel Enhanced Arithmetic Optimization Algorithm for Global Optimization

A Novel Enhanced Arithmetic Optimization Algorithm for Global Optimization

Improved Symbiotic Organisms Search Algorithm for Optimal Operation of Active Distribution Systems Incorporating Renewables and Emerging Data‐Center Resources

A Complex-Valued Encoding Multichain Seeker Optimization Algorithm for Engineering Problems

Contact Info

Product

Resources

About