Artificial Bee Colony-Genetic Algorithm In Job-Shop Scheduling Research

In nearly a century, with the development of science and technology, enterprises increasingly fierce competition, how to change the old production and management mode to adapt to the requirements of modern production, and further enhance the competitiveness of enterprises, enterprises have become an important problem we are facing. In practical production, effective scheduling and optimization technology is the foundation and key for an advanced manufacturing and improving the production efficiency.By improving the production scheduling scheme, it can effectively improve the production efficiency of enterprises, enhance the market competition ability of the enterprise. Job shop scheduling problem is to solve the problem that how to use the limited resources to meet a variety of production constraints, determine the the order and time of the workpiece and processing equipment, and make the index optimal. As a simplified model of production scheduling, Job shop scheduling problem has the important practical significance.In this article, with the Genetic Algorithm and the Bee Conoly Algorithm, we design and implement a new hybrid algorithm, Artificial Bee Colony-Genetic Algorithm, using the algorithm to solve the Job-Shop scheduling problem. The basic principle of the Bee Conoly-Genetic Algorithm is to combinate the Genetic Algorithm with Artificial Bee Colony algorithm, use the respective advantages of the two kinds of algorithms, while overcoming their defects, and ultimately realize the complementary advantages, to get a more efficient optimization algorithm. The Genetic Algorithm has some disadvantages such as poor local search ability, When solving in a certain range, it often does a lot of useless redundancy iteration, with low solving efficiency, prone to premature convergence problem, and the Bee Colony Algorithm has strong local searching ability and faster convergence speed, so use the Bee Colony Algorithm-Genetic Algorithm to overcome the shortcomings of the Genetic Algorithm is feasible. This article is mainly to study about the organic combination of the two kinds of algorithms, and put forward a complete algorithm theory, established a Bee Colony-Genetic Algorithm.Finally, ABCGA is applied to make a shop scheduling simulation system, the classic instance of Job-Shop problem is used to assess the efficiency of the algorithm, and the algorithm is applied to solve Job-Shop scheduling problem, results show that the convergence of ABCGA is more efficient, faster and the new algorithm is practical and efficient in solving Job-Shop scheduling problem.