Exploration of multi scene task scheduling and simulation experiment platform for materials transportation robots system

Abstract

Objective: Verify the feasibility of the task scheduling and algorithm test platform of the materials transportation robots system based on the actual order data. Methods: This paper discusses the design of simulation experiment through the independently developed platform, focusing on the typical scenarios of pharmaceutical logistics. Aiming at the logistics scenario of task allocation strategy of multi robot with task classification, the Memory Elite Population based Catastrophe Adaptive Large Neighborhood Search(MEPCALNS) algorithm is designed. Results: Compared with ALNS algorithm, the efficiency of MEPCALNS algorithm is increased by 3.16% on average. Conclusion: By means of algorithm optimization research and simulation operation comparison of various scenarios. The value of the platform in algorithm verification is proved, which shows the effectiveness of MEPCALNS algorithm in typical scenarios.

Keywords

• materials transportation robots system
• task scheduling
• simulation experiment platform
• algorithm optimization