Research On Job Shop Scheduling Problem By Ant Colony Optimization And Tabu Search Fusion Algorithm

Shop floor scheduling is an essential aspect of modern manufacturer's managerial activities.The research and application of scheduling method and optimization technique bearing a significant effect on manufacture process.This paper reviewed the research status at home and abroad,conducted a research on job shop scheduling problem via Ant colony optimization(ACO)and tabu search(TS)algorithm.The main content can be separated into 3 parts,first part is modifing and merging algorithms target on JSSP,which include: applied four sub-strategies which are “adaptive pheromone quantity update method”,“inner-pheromone update method”,“local optimum breakout mechanism” and “modified state transition rule” to cope with ACO's “long searching time,slow convergence”,“tendency to fall into local optimum” and “solutions' inferiority”.Then a modified tabu search algorithm based on critical block neighborhood structure via critical path has been proposed.Finally,based on the respective advantage of ACO and TS,a fusion algorithm has been designed.The simulation on all LA instances has proved its performance superiority.The second part include employing different tactics to copy with machine flexibility,multi-object scheduling and dynamic event that may happen in real production process,proposed a method to solve flexible dynamic multi-object JSSP and verified its effectiveness through simulation.Third,according to enterprise's demand,a shop floor scheduling system has been designed.This paper illustrated its demand,structure,performance requirement,running environment and presented the prototype.