NSGA-Ⅱ Based on Multi-Population for Multi-AGV Scheduling in Cigarette Factory
Aiming at the contradictory between the number of AGVs and the operating efficiency during the process of AGV application,the multi-AGV scheduling optimization model for the ingredient transportation system of a cigarette factory is established,to minimize the vehicle number and the makesapn.To solve this problem,a multi-population NSGA-Ⅱ algorithm is designed,where a variety of crossover operators are introduced to strengthen the global exploration ability of the algorithm,three subpopulations are constructed to explore Pareto optimal solutions from different directions,and the heuristic neighbor-hood search strategy is designed.According to the practical working environment,four test instances with different scales are constructed.By comparing with other classical multi-objective optimization algorithms,it is verified that the proposed algorithm can obtain the Pareto solution set with good convergence and distribution,providing decision schemes for AGV scheduling.
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