Metaheuristic

Algorithm

Backtracking

Imperialist competitive algorithm

Probabilistic logic

Computer science

Mathematical optimization

Meta-optimization

Beam search

Image segmentation

Regression analysis

Best-first search

Segmentation

Mathematics

Test case

Beam stack search

Artificial intelligence

Hybrid algorithm (constraint satisfaction)

Constraint satisfaction

Heuristic

Search algorithm

Constraint logic programming

Optimization problem

Test suite

Machine learning

Expert Systems with Applications

A novel algorithm called Poplar Optimization Algorithm (POA) is developed in this paper to solve continuous optimization problems. The algorithm mimics the sexual and asexual propagation mechanism of poplar, where the basic philosophy of how to execute sexual and asexual propagation for individuals is detail designed in the algorithm. Mutation strategy of backtracking search algorithm is adopted in POA to maintain the diversity in a certain degree. The performance of POA algorithm is tested on 25 functions from the CEC2005 test suite and 30 functions from the CEC2017 test suite with different features. The results of POA are compared with some other population-based algorithms in terms of the quality and efficiency. Finally, the proposed algorithm is used to find the optimal threshold for image segmentation. The results indicate that the poplar optimization algorithm can obtain competitive or superior performance.

Poplar optimization algorithm: A new meta-heuristic optimization technique for numerical optimization and image segmentation