A Flower Pollination Optimization Algorithm Based on Cosine Cross-Generation Differential Evolution
The flower pollination algorithm (FPA) is a novel heuristic optimization algorithm inspired by the pollination behavior of flowers in nature. However, the global and local search processes of the FPA are sensitive to the search direction and parameters. To solve this issue, an improved flower pollin...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-01-01
|
| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/23/2/606 |
| _version_ | 1797437341607919616 |
|---|---|
| author | Yunjian Jia Shankun Wang Liang Liang Yaxing Wei Yanfei Wu |
| author_facet | Yunjian Jia Shankun Wang Liang Liang Yaxing Wei Yanfei Wu |
| author_sort | Yunjian Jia |
| collection | DOAJ |
| description | The flower pollination algorithm (FPA) is a novel heuristic optimization algorithm inspired by the pollination behavior of flowers in nature. However, the global and local search processes of the FPA are sensitive to the search direction and parameters. To solve this issue, an improved flower pollination algorithm based on cosine cross-generation differential evolution (FPA-CCDE) is proposed. The algorithm uses cross-generation differential evolution to guide the local search process, so that the optimal solution is achieved and sets cosine inertia weights to increase the search convergence speed. At the same time, the external archiving mechanism and the adaptive adjustment of parameters realize the dynamic update of scaling factor and crossover probability to enhance the population richness as well as reduce the number of local solutions. Then, it combines the cross-generation roulette wheel selection mechanism to reduce the probability of falling into the local optimal solution. In comparing to the FPA-CCDE with five state-of-the-art optimization algorithms in benchmark functions, we can observe the superiority of the FPA-CCDE in terms of stability and optimization features. Additionally, we further apply the FPA-CCDE to solve the robot path planning issue. The simulation results demonstrate that the proposed algorithm has low cost, high efficiency, and attack resistance in path planning, and it can be applied to a variety of intelligent scenarios. |
| first_indexed | 2024-03-09T11:18:49Z |
| format | Article |
| id | doaj.art-0b318ff930c44efbb3c263533a69bb76 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T11:18:49Z |
| publishDate | 2023-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-0b318ff930c44efbb3c263533a69bb762023-12-01T00:24:30ZengMDPI AGSensors1424-82202023-01-0123260610.3390/s23020606A Flower Pollination Optimization Algorithm Based on Cosine Cross-Generation Differential EvolutionYunjian Jia0Shankun Wang1Liang Liang2Yaxing Wei3Yanfei Wu4School of Electronics and Communication Engineering, Chongqing University, Chongqing 400044, ChinaSchool of Electronics and Communication Engineering, Chongqing University, Chongqing 400044, ChinaSchool of Electronics and Communication Engineering, Chongqing University, Chongqing 400044, ChinaSchool of Electronics and Communication Engineering, Chongqing University, Chongqing 400044, ChinaSchool of Electronics and Communication Engineering, Chongqing University, Chongqing 400044, ChinaThe flower pollination algorithm (FPA) is a novel heuristic optimization algorithm inspired by the pollination behavior of flowers in nature. However, the global and local search processes of the FPA are sensitive to the search direction and parameters. To solve this issue, an improved flower pollination algorithm based on cosine cross-generation differential evolution (FPA-CCDE) is proposed. The algorithm uses cross-generation differential evolution to guide the local search process, so that the optimal solution is achieved and sets cosine inertia weights to increase the search convergence speed. At the same time, the external archiving mechanism and the adaptive adjustment of parameters realize the dynamic update of scaling factor and crossover probability to enhance the population richness as well as reduce the number of local solutions. Then, it combines the cross-generation roulette wheel selection mechanism to reduce the probability of falling into the local optimal solution. In comparing to the FPA-CCDE with five state-of-the-art optimization algorithms in benchmark functions, we can observe the superiority of the FPA-CCDE in terms of stability and optimization features. Additionally, we further apply the FPA-CCDE to solve the robot path planning issue. The simulation results demonstrate that the proposed algorithm has low cost, high efficiency, and attack resistance in path planning, and it can be applied to a variety of intelligent scenarios.https://www.mdpi.com/1424-8220/23/2/606flower pollination algorithm (FPA)cross-generationdifferential evolution (DE)external archiveroulette wheelrobot path planning |
| spellingShingle | Yunjian Jia Shankun Wang Liang Liang Yaxing Wei Yanfei Wu A Flower Pollination Optimization Algorithm Based on Cosine Cross-Generation Differential Evolution Sensors flower pollination algorithm (FPA) cross-generation differential evolution (DE) external archive roulette wheel robot path planning |
| title | A Flower Pollination Optimization Algorithm Based on Cosine Cross-Generation Differential Evolution |
| title_full | A Flower Pollination Optimization Algorithm Based on Cosine Cross-Generation Differential Evolution |
| title_fullStr | A Flower Pollination Optimization Algorithm Based on Cosine Cross-Generation Differential Evolution |
| title_full_unstemmed | A Flower Pollination Optimization Algorithm Based on Cosine Cross-Generation Differential Evolution |
| title_short | A Flower Pollination Optimization Algorithm Based on Cosine Cross-Generation Differential Evolution |
| title_sort | flower pollination optimization algorithm based on cosine cross generation differential evolution |
| topic | flower pollination algorithm (FPA) cross-generation differential evolution (DE) external archive roulette wheel robot path planning |
| url | https://www.mdpi.com/1424-8220/23/2/606 |
| work_keys_str_mv | AT yunjianjia aflowerpollinationoptimizationalgorithmbasedoncosinecrossgenerationdifferentialevolution AT shankunwang aflowerpollinationoptimizationalgorithmbasedoncosinecrossgenerationdifferentialevolution AT liangliang aflowerpollinationoptimizationalgorithmbasedoncosinecrossgenerationdifferentialevolution AT yaxingwei aflowerpollinationoptimizationalgorithmbasedoncosinecrossgenerationdifferentialevolution AT yanfeiwu aflowerpollinationoptimizationalgorithmbasedoncosinecrossgenerationdifferentialevolution AT yunjianjia flowerpollinationoptimizationalgorithmbasedoncosinecrossgenerationdifferentialevolution AT shankunwang flowerpollinationoptimizationalgorithmbasedoncosinecrossgenerationdifferentialevolution AT liangliang flowerpollinationoptimizationalgorithmbasedoncosinecrossgenerationdifferentialevolution AT yaxingwei flowerpollinationoptimizationalgorithmbasedoncosinecrossgenerationdifferentialevolution AT yanfeiwu flowerpollinationoptimizationalgorithmbasedoncosinecrossgenerationdifferentialevolution |