Based On Hybrid Ant Colony Algorithm For Job Shop Scheduling Problem To Solve

With the increase in global competition, Multi-product and small-batch production which is made to order will be the main production mode of 21 century. Correspondingly, manufactory is on the development to lean production and agile manufacturing. In this condition, how to plan and schedule becomes the key issue to make the manufacture process smoothly and efficiently. It is very important to research on effective scheduling and optimization to improve productivity and reduce cost. So more and more researchers pay attention to this research.The Job Shop Scheduling Problem is the core in production and operational management to maximize business performance with high efficiency and low production costs. Consequently, the research of JSSP has been an attractive subject in academic and industrial communities, and has great importance in engineering applications.Ant Colony Algorithms (ACA) is a novel evolutionary algorithm, derived from the foraging behavior of real ants of nature, which can find the shortest path between a food source and their nest. Its main characteristics are positive feedback, distributing computing and the use of a constructive heuristic. And as a new branch of computational intelligence and swarm intelligence, it has attracted more and more attention.This paper begins with an introduction to the concept, characteristics, objectives and critical positions of JSSP. The paper also gives a brief survey on the current development of JSSP models and solutions. In this dissertation, the model, algorithm and performance of Ant Colony Algorithms are introduced. And then some improved Ant Colony Algorithms are advanced and simulated. The major contributions are as follows: The paper proposes a new JSSP neighborhood structure that can reduce the size of space with the traditional neighborhood structure; According to the crucial role of pheromone intensity in Ant Colony Optimization, methods are proposed by strengthening the pheromone intensity of the ants with the best solutions in the current or global ant colonies; The paper simplify parameter setting and adjust some parameters dynamically; Through a phased Neighborhood Transformation ,the paper proposes a new hybrid algorithm.Through object-oriented technology, this paper achieve core scheduling functions, presents a model system based on the MVC design method. The simulation result shows that the improved ant colony algorithm can search the better solution more quickly.The paper has some reference value on research of the Ant Colony Algorithms and makes some contribution to the development of JSSP in the theoretical research and the applied value.