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Stacking order planning method based on adaptivesimulated annealing genetic algorithm(PDF)


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Stacking order planning method based on adaptivesimulated annealing genetic algorithm
Xu MingjiLi ShengChen QingweiGuo JianWu Yifei
School of Automation,Nanjing University of Science and Technology,Nanjing 210094,China
rectangular coordinate palletizing robots stacking order decisive variables mathematical models adaptive simulated annealing genetic algorithm
TP18; TP301.6
In order to optimize the robot stacking sequence of rectangular axes and save stacking time,avoid influences like different kinds of material boxes’ random stacking and random position choice on piling work,this paper builds up a mathematical model involving material boxes choice and stacking position distribution and designs a two-level heuristic algorithm based on an adaptively simulated annealing genetic algorithm to solve the problems.We take unstacking sequence,stacking sequence,and stacking area as decisive variables and aim to make the shortest route of stacking and unstacking process.This paper makes simultaneous optimization on the model and gets a set of optimal stacking sequence according to the simulation of 104 material boxes.The simulation results show that,compared with a set of random stacking sequence,material boxes’ choice and stacking position distribution can effectively cut down working route and working time,which means that the model and algorithm are feasible and effective.


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Last Update: 2017-08-31