scholarly journals An Iterated Hybrid Local Search Algorithm for Pick-and-Place Sequence Optimization

Symmetry ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 633 ◽  
Author(s):  
Jinsheng Gao ◽  
Xiaomin Zhu ◽  
Anbang Liu ◽  
Qingyang Meng ◽  
Runtong Zhang
Keyword(s):  
Integer Programming ◽  
Local Search ◽  
Large Scale ◽  
Programming Model ◽  
Search Algorithm ◽  
Local Search Algorithm ◽  
Pick And Place ◽  
Feeder Assignment ◽  
High Computational Efficiency ◽  
The Greedy Algorithm

This paper shows the results of our study on the pick-and-place optimization problem. To solve this problem efficiently, an iterated hybrid local search algorithm (IHLS) which combines local search with integer programming is proposed. In the section of local search, the greedy algorithm with distance weight strategy and the convex-hull strategy is developed to determine the pick-and-place sequence; in the section of integer programming, an integer programming model is built to complete the feeder assignment problem. The experimental results show that the IHLS algorithm we proposed has high computational efficiency. Furthermore, compared with the genetic algorithm and the memetic algorithm, the IHLS is less time-consuming and more suitable in solving a large-scale problem.

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