Co-operative Ant Colony Optimization Algorithm In Production Scheduling Problems

As the core of the corporation production management, scheduling problem is always concerned by people. Production scheduling is problem which determining the reasonable market decision-making and allocating the limited material resources to different tasks, making the intended objective optimal or near maximization optimal when the production task is given. How to optimize the production scheduling efficiently is now a key to improve the productivity and economic benefit for the corporation. Flow shop scheduling problem is not only a classical scheduling problem but also a NP-hard combinatorial optimization problem, the analyze to which has both theoretical meaning and practical value.The main research of this dissertation can be summarized as follows:(1)Ant colony algorithm is a new developed optimization algorithm, which showed advantage in the combinatorial optimization problem solution after solved the classical TSP problem. As the algorithm improved by people, it is used widely. This thesis gives a new improved method-cooperative ant colony optimization algorithm, based on the basic ant colony algorithm. The new algorithm accomplish communication from two different ant colony species, after choose the certain best values from the two species and renew the pheromone,thereby, the rate of convergence is obviously accelerate, and increases the chance to find the best value.(2) Research on some different Flow Shop scheduling problems have been carried in batch processes. The Flow Shop scheduling problem with Zero-Wait has been studied. According to it own characteristic, the corresponding model has been set up, computing by cooperative ant colony optimization algorithm. The simulation results of different problems demonstrate the superiority of the model and proposed algorithms.(3)The Flow Shop scheduling problem with uncertain factors has been investigated. The triangular fuzzy number has been applied to describe the uncertain processing time of products in real production environment. Model has been built based on fuzzy programming theory and computed by cooperative ant colony optimization algorithm. The simulation results of different problems demonstrate the superiority of the model and proposed algorithms.