Search

With the development of intelligent logistics technology, some companies began to use robots instead of humans to load cargo. This paper studies a novel container loading problem based on robotic loader system (CLP-RLS). Different from the existing robot-packable pattern in the literature, the robotic loader system in this paper consists of a depalletizing robot, an automatic telescopic roller line and a loading robot, in which the loading robot will enter the carriage along with the automatic telescopic roller line. In CLP-RLS, it is necessary to consider not only many practical constraints already in the literature, including load balancing, orientation, stability, and multi-drop but also two new constraints related to robotic loader system: pallet continuity constraint (the loading sequence of cargo on the same pallet is continuous) and robot position constraint (the robot can only load cargo incrementally from the front to the back of the truck). Due to the difficulty in modeling CLP-RLS and the large scale of the real-case instances, we present a tree search approach based on wall-building to solve CLP-RLS, intending to find a feasible loading scheme for the RLS to minimize the length required to load all cargo. The effectiveness of the proposed approach is verified through both real-case instances and numerical instances. • A novel container loading problem based on robotic loader system is studied. • A tree search approach based on wall-building is proposed to solve this problem. • The effectiveness of the proposed approach is verified through real-case instances. • The proposed approach can support the decision-making of the truck delivery route. [ABSTRACT FROM AUTHOR]

Schematic illustration of pesticide residues in spinach leaves detected by SERS imaging after detergent washing and verified by HPLC. [Display omitted] • We use SERS imaging to evaluate pesticide removal effect of different detergents. • 5:5 LAS-APG at 0.2 % had the strongest combined effect. • Combined effect of different mixed detergent was revealed by surface tensions. Pesticide residues on vegetables could be removed by commercial detergents to guarantee food safety, but the removal efficiencies of different formulations of detergents need to be further investigated. In this work, surface enhanced Raman scattering (SERS) imaging method due to its good space resolution as well as high sensitivity is used to track the thiram residue, and evaluate the pesticide removing efficiencies by mixtures of several surfactants at different ratios. Sodium linear alkylbenzene sulphonate-alkyl glycoside (LAS-APG) with the ratio at 5:5 and the concentration at 0.2 % show the best removing effect. In addition, HPLC method is employed to validate the results of SERS imaging. Furthermore, LAS-APG mixture could be efficiently washed out from the leaves through simple household cleaning, meaning no secondary contamination. It is perspective that SERS imaging is an effective technique to explore the effect of fruit and vegetable detergents in removing pesticide residues. [ABSTRACT FROM AUTHOR]