Application Of Improved Hybrid Ant Colony Genetic Algorithm In Plant Management Information System

Modern equipment management based on device life for the object, including the form of physical movement of equipment, as planning, design, manufacture, purchase, installation, use, maintenance, alteration, renovation until retirement. And included the value of the equipment state of motion, as the initial investment of equipment, maintenance expenses, depreciation, renovation financing, accumulation, expenditure management, etc. To maintain equipment in good condition and continue to improve the technical quality of equipment, ensure the effective use of equipment and maximum economic benefits. In this paper, for the shortcomings of the previous equipment management, design and implementation of common intelligence check path generation, an efficient optimization intelligent algorithm is necessary.Intelligence check path generation problems issue are very complicated in many manufacturing enterprises, and difficult to solve with traditional optimization methods. In recent years, hybrid ant colony algorithm has been studied as an optimization algorithm for solving path problems by the majority of scholars. Hybrid ant colony algorithm has been did a lot of research and analysis in this paper. Find that the original Hybrid Ant Colony Genetic Algorithm has a problem that the effect of the genetic algorithm is not obvious, and easy to premature convergence. An improved Gene Volume Control Hybrid Ant Colony Genetic Algorithm can effectively improve the number of genetic basis, and the ability to generate the global optimal solution. Generating dynamic mutation probability with dynamic analysis of genetic fitness also can improve the ability to generate the global optimal solution. Using the principles of elite cross can protect the good genes from the deterioration made by impact of crossover and mutation.Because of TSP problems and mathematical models which are abstracted from check path generation in actual production process are very similar, by using the TSP problem library TSPLIB in Matlab prove that the new algorithm is effective and efficient. New algorithm can successfully search for the optimal solution of the problem and the local optimal solution set.For the practical problems of a metallurgical enterprise, an intelligent check plant information management system has been designed and implemented based on JAVA technology in this paper. The new algorithm has been used in this system for the practical intelligence check path generation problem. It can generate the check path for work demand of a single checker. The results are feasible and effective.