Novel ant colony optimization algorithm for Job-Shop scheduling problem
一种求解Job-Shop调度问题的新型蚁群算法

Aiming at the problem of all possible states and the inventory holding cost not completely considered in general dynamic facility location model, this paper developed a new model. Firstly, obtained the formula of inventory cost in per period with storage and traffic capacity constraints through two steps approximately method. Then, gave the formulas of opening, operation, closing and reopening cost in planning horizon, and developed a new dynamic facility location model. Finally, solved the model by genetic algorithm, clone selection algorithm, particle swarm optimization respectively, and compared the capacities of finding optimal solution, stability, counting speed and astringency between these algorithms. The results of numerical example show that the model is effective and the genetic algorithm is the most suitable for the problem.