Research Of Flow Shop Scheduling Problem Based On Improved Artificial Fish Swarm Algorithm

The nature of the scheduling problem is the process of a rational allocation of resources. The aim of scheduling is allocate the limited resources to multiple targets to optimize one or more objectives. Optimized production scheduling scheme can improve production efficiency> reduce production cost and economic benefits for the company. The flowshop problem is one of the main types of production scheduling and attracts more attention from many scholars. At this thesis, we improved the basic ABC,applying it to flowshop problem and the results turn out to be better. The main contributions of this dissertation are listed below.(1) In order to overcome the shortcomings of ABC, we introduce the improved ABC with local search and chaos. By testing standard function, we know that the convergence rate and the ability of global search and escaping from local optima are better than ABC.(2) After the analysis of the permutation flowshop, we apply IABC to permutation flowshop. Use the SPV rules to connect the continuous and discrete domain based on the coding of job permutation and initialize the solution with NEH. The simulation results show that IABC is better than ABC and PSO.(3) Thinking of the characteristics of lot-streaming flowshop, we introduce a discrete artificial bee colony algorithm. The DABC use the coding of job permutation and have the idea of local search and NEH. The NEH heuristic algorithm can improve the quality of initialized solution and local search can enhance the ability of searching the optimum. The simulation results show that the DABC is better.