Reducing time in order to obtain the best solution for a combinatorial optimization problem is a big problem in today’s paradigm of optimization. One way to reduce time to acquire best solution for a combinatorial optimization problem is proposed in this paper. Researchers used the population’s visualization power to see path to traverse and obtain additional heuristic information in order to enhance their position to achieve their goal in a foggy environment. The proposed algorithm is tested on Rosenbrock function introduced by Howard H. Rosenbrock in 1960. This new optimization algorithm reduces the cost from 100 to 54.6342 when applied on the objective function of Rosenbrock using MATLAB 8.5 - R2015a.