A Hybrid APM-CPGSO Approach for Constraint Satisfaction Problem Solving: Application to Remote Sensing

Constraint satisfaction problem (CSP) has been actively used for modeling and solving a wide range of complex real-world problems. However, it proven that developing efficient methods CSP, especially large problems, is very difficult challenging. Existing complete problem-solving are in most cases unsuitable. Therefore, proposing hybrid CSP-based increasing interest the last decades. This paper aims at novel approach combines incomplete CSP problem-solving. The proposed takes advantage group search algorithm (GSO) constraint propagation (CP) to solve problems related remote sensing field. To best our knowledge, this represents first study proposes hybridization between an improved version GSO CP resolution constraint-based Experiments have conducted object recognition satellite images. Results show good performances terms convergence running time method compared existing state-of-the-art methods.