An Effective Iterated Greedy Algorithm for Multi-Robot Task Allocation and Scheduling Problem

With the swift progress of intelligent and unmanned technologies, new opportunities and challenges have emerged for smart agriculture. The use of intelligent robots in various farming activities is becoming increasingly prevalent in agricultural production. This paper examines the issue of task allocation and scheduling for multiple agricultural robots working within the context of a smart farm. The multi-robot task allocation and scheduling problem (MRTASP) has been confirmed to be NPhard problem. An effective iterated greedy (EIG) algorithm is presented to decrease the maximum completion time of the MRTASP in this study. In the EIG algorithm, to better exploit the specificity of the problem, the HPF2 algorithm is used to create an efficient initialization approach. A reconstruction method is proposed to improve the answer achieved at each iteration. The performance of EIG algorithm is tested on 720 instances. The EIG algorithm is useful for solving the MRTASP and its completion time is as short as possible, according to the results of the experiments.