Providing new meta-heuristic algorithm for optimization problems inspired by humans behavior to improve their positions
Seyedmoslem Seyedmirzaee · 2013
Nowadays, meta-heuristic algorithms have earned special position in optimization problems, particularly nonlinear programming. In this study, a new meta -heuristic algorithm called Improvement of position (IMPRO Algorithm) is recommended to solve the opti mization problems. This algorithm, similar to other heuristic and meta-heuristic algorithms starts with production of random numbers. However, the aforementioned algorithm is inspired by humans’ behavior to enhance the position which coincidentally detects the best position with respect to various conditions. Subsequently, a position with the least standard deviation (0.01) is created surrounding random numbers around the situationin the form of normal distribution. Afterwards, the new top position is cons idered and the two positions are compared and the top position is determined. Thus the conditions which created the best position are situated as the motion factors. Naturally, the motion direction is toward the opposite direction of the lower position. Nthis algorithm changes a response during the search process and solves the problem by utilizing the firm decisions.