Providing new meta-heuristic algorithm for optimization problems inspired by humans' behavior to improve their positions

Nowadays, meta-heuristic algorithms have earned special position in optimization problems, particularlynonlinear programming. In this study, a new meta-heuristic algorithm called "Improvement of position(IMPRO Algorithm)" is recommended to solve the optimization problems. This algorithm, similar to otherheuristic and meta-heuristic algorithms starts with production of random numbers. However, theaforementioned algorithm is inspired by humans’ behavior to enhance the position which coincidentallydetects the best position with respect to various conditions. Subsequently, a position with the least standarddeviation (0.01) is created surrounding random numbers around the situation in the form of normaldistribution. Afterwards, the new top position is considered and the two positions are compared and the topposition is determined. Thus the conditions which created the best position are situated as the motionfactors. Naturally, the motion direction is toward the opposite direction of the lower position. Next, thisalgorithm changes a response during the search process and solves the problem by utilizing the firmdecisions.