Optimization of machine layout based on genetic algorithm

To solve the machine layout problem, a multi-objective optimization model was constructed. And a combination mutation strategy, combined with the best individual mutation and the random mutation, was designed to remedy the defects of the present genetic algorithms for site layout problems. At the beginning of combination mutation, the best individual mutation was executed. If a better individual was generated, the worst individual in current population was replaced by the new one. Otherwise, the random mutation was executed on a random selected individual. Based on the combination mutation strategy, an improved genetic algorithm was also proposed to solve the problem of machine layout. Simulation experiments prove that the combination mutation strategy achieves solutions not inferior to the solutions of the random mutation in obviously shorter time. A comparative analysis further verifies the efficiency of the proposed algorithm.