Genetic annealing with efficient strategies to improve the performance for the NP-hard and routing problems

problem which cannot be solved in polynomial time for asymptotically large values of and travelling salesman problem (TSP) is important in operations research and theoretical computer science. In this paper a balanced combination of genetic algorithm and simulated annealing has been applied. To improve the performance of finding an optimal solution from huge search space, we have incorporated the use of tournament and rank as selection operators, and inver-over operator mechanism for crossover and mutation. This proposed technique is applied for some routing resource problems in a chip design process and a best optimal solution was obtained, and the TSP appears as a sub-problem in many areas and is used as a benchmark for many optimisation methods.