On manipulation of initial population search space in heuristic algorithm through the use of parallel processing approach

Increasing use of heuristic algorithms in various fields of science causes numerous modifications of the original algorithms in need for better performance and efficiency. The main problem of heuristics is time required to find optimal solution. For this purpose, we propose to use parallel processing in the initial phase of heuristic methods to decrease computing time. Implemented technique models migration of individuals by adjusting initial population to required conditions. Proposed approach is simulating parallel processes that take place in human brain while solving tasks. In this case, human intelligence is working parallel on various aspects of the problem to compare them in the end before final decision. Proposed approach is simulating this parallelization of thinking threads in the process of optimization. Presented experimental tests have been carried out and discussed in terms of advantages and disadvantages.