Application Research Of Permutation Flow Shop Scheduling Problem Based On Improved Whale Algorithm

Permutation flow-shop scheduling realizes the minimization of the maximum completion time by reasonably arranging the processing sequence of workpieces on the machine,so as to improve production efficiency and machine utilization.However,permutation flow shop scheduling problem is essentially an integer programming problem,and it is a NP-Hard problem.Its solution method has been concerned by researchers.Therefore,this paper takes the permutation flow shop scheduling problem as the research object,and uses the whales swarm algorithm to solve the permutation shop scheduling problem.The main work of this paper includes:Firstly,the traditional whales swarm algorithm realizes searches for prey by randomly selecting a point in the solution space as the prey position,and then performing the surround operation.Since the location of prey is chosen randomly,the location of whale generated by enclosure behavior is also random,so the newly generated whale may fall in the area where the density of the whales is high,which is not conducive to improving the global search ability of the algorithm.In order to overcome the above problems,this paper proposes to adjust the location of whale based on crowding detection results,so as to improve the probability of whale landing in sparse areas,and to some extent,balance the global exploration and local exploration of whale swarm algorithm.Secondly,the whale swarm algorithm is proposed to solve the continuous problem,but the actual permutation flow shop scheduling problem belongs to the integer programming problem.For this reason,this paper uses integer coding sorted by whale location size to establish the one-to-one correspondence between whale location and scheduling feasible solution,and applies the improved whale algorithm to solve the permutation flow shop scheduling problem.Thirdly,in order to further improve the ability of whale swarm algorithm to solve integer programming problems,this paper improves the strategy of searching for prey in whale swarm algorithm,proposes a local search strategy(swap method,insertion method and reverse sequence method)adapting to integer programming to generate whale locations,and adopts a selection strategy based on crowding degree to select whales,which improves the diversity and global search capability of whale swarm algorithm to a certain extent.Finally,in order to verify the effectiveness of the proposed algorithm,the algorithm is applied to solve the standard scheduling problems of Taillard class and car class in different scales.The simulation results show the effectiveness of the proposed algorithm.