A new cutting-edge method recently garnered interest is image encryption utilizing a genetic approach. Currently, most genetically based picture encryption algorithms use fixed parameters to encrypt images, ignoring any image-representative properties. This research led to PixAdapt, a novel adaptive picture encryption technique. It is being re-engineered such that the fitness of the encrypted picture can be determined using UACI, and the relevant parameters may be adjusted using hereditary hill climb or pretend annealing. Pseudorandom numbers have been generated using a variety of chaos-based maps, including the Logistic, Rossler, Henon, and Tent maps, as well as the linear feedback shift register. The PixAdapt algorithm uses the theory of confusion and diffusion to further ensure that the plaintext and ciphertext images are completely dissimilar. This is the first instance of optimizing picture encryption settings using metaheuristic search algorithms. Finding the best possible UACI value, the hereditary hill climb algorithm encrypts all of the photos. Fitness enhancement, limit evolution, arithmetical analysis, and encryption quality testing have all been conducted on the method. When it comes to effectively encrypting images, PixAdapt is one of a kind and has shown that the UACI encryption parameter is a good match.