A Two-Objective ILP Model of OP-MATSP for the Multi-Robot Task Assignment in an Intelligent Warehouse

Applied Sciences

Yunhong Xu¹  Yanjie Li¹  Jianqi Gao¹  Shaohua Lv¹ 

[1] School of Mechanical Engineering and Automation, Harbin Institute of Technology (Shenzhen), Shenzhen 518071, China;

关键词: multi-robot task assignment;    intelligent warehouse;    OP-MATSP;    ILP;    genetic algorithm;   

DOI  :  10.3390/app12104843

来源: DOAJ

【 摘 要 】

Multi-robot task assignment is one of the main processes in an intelligent warehouse. This paper models multi-robot task assignment in an intelligent warehouse as an open-path multi-depot asymmetric traveling salesman problem (OP-MATSP). A two-objective integer linear programming (ILP) model for solving OP-MDTSP is proposed. The theoretical bound on the computational time complexity of this model is $O(n!)$. We can solve the small multi-robot task assignment problem by solving the two-objective ILP model using the Gurobi solver. The multi-chromosome coding-based genetic algorithm has a smaller search space, so we use it to solve large-scale problems. The experiment results reveal that the two-objective ILP model is very good at solving small-scale problems. For large-scale problems, both EGA and NSGA3 genetic algorithms can efficiently obtain suboptimal solutions. It demonstrates that this paper’s multi-robot work assignment methods are helpful in an intelligent warehouse.

【 授权许可】

Unknown