## 5 Conclusions  
This paper studies a stochastic variant of the 2L-VRP, where each customer has a probability of presence and customers' demands are considered non-stackable rectangular-shape items. A stochastic programming model of the 2L-VRPSC has been established based on Monte Carlo simulation and scenario analysis. An enhanced adaptive tabu search algorithm incorporating a MOBFS packing heuristic has been proposed, which solved four classes of 2L-VRPSC with different loading configurations, namely, unrestricted ori \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline  & \multicolumn{2}{c}{**EATS**} & \multicolumn{2}{c}{**ATS**} & \multicolumn{2}{c}{**ETS**} \\ \cline{2-10}
**Instance** & **Cost** & **Time (s)** & **Cost** & **Time (s)** & **Gap (\%)** & **Cost** & **Time (s)** & **Gap (\%)** \\ \hline
1 & 282.95 & 712 & 282.95 & 715 & 0.00 & 282.95 & 716 & 0.00 \\
3 & 401.81 & 801 & 404.82 & 792 & 0.75 & 404.59 & 797 & 0.69 \\
5 & 383.29 & 741 & 384.38 & 734 & 0.28 & 383.29 & 745 & 0.00 \\
7 & 746.50 & 938 & 741.12 & 904 & \(-\)0.72 & 745.46 & 943 & \(-\)0.14 \\
9 & 621.73 & 1356 & 628.65 & 1309 & 1.11 & 627.76 & 1307 & 0.97 \\
11 & 725.40 & 1745 & 735.24 & 1702 & 1.36 & 737.29 & 1737 & 1.64 \\
13 & 2634.99 & 1400 & 2699.30 & 1373 & 2.44 & 2663.13 & 1407 & 1.07 \\
15 & 1079.00 & 1901 & 1082.78 & 1879 & 0.35 & 1074.14 & 1921 & -0.45 \\
17 & 907.35 & 1711 & 915.84 & 1662 & 0.94 & 920.51 & 1720 & 1.45 \\
19 & 792.11 & 1799 & 806.79 & 1779 & 1.85 & 799.34 & 1758 & 0.91 \\ Ave & 857.5 & 1310.4 & 868.2 & 1284.9 & 0.84 & 863.85 & 1305.0 & 0.61 \\ \hline \hline \end{tabular}
\end{table} 
Table 10: Comparison of average results between EATS, ATS and ETS algorithms, where “Gap” denotes the percentage gap between the proposed EATS and ATS or ETS. ented loading (2\(|\)U\(0\)\(|\)L), unrestricted rotated loading (2\(|\)UR\(|\)L), sequential oriented loading (2\(|\)SO\(|\)L) and sequential rotated loading (2\(|\)SR\(|\)L). The performance of the proposed approach is verified through experiments on the 2L-VRP and 2L-VRPSC instances, which are compared with existing methods. The experimental results demonstrate the effectiveness and versatility of solving the 2L-VRPSC and 2L-VRP. The comparison between existing methods shows the efficiency of the proposed EATS-MOBFS method for solving the 2L-VRP with different loading configurations, except for some large-scale instances. Moreover, the proposed model is capable of providing more practical solutions for real-life scenarios with uncertain information. Meanwhile, the comparative results indicate that the adaptive weight adjustment and diversification mechanism have a positive impact on the interplay between intensification and diversification. Observations show that a lower presence probability of customers and a larger number of customers will increase the transportation cost in the 2L-VRPSC. This work has opened up several directions for future research. First, although this research's high-quality solutions have been obtained by the proposed approach, there is still room for improvement. Such improvements can include further enhancing the neighborhood operators in EATS and introducing more exclusive packing strategies. Second, in this paper, we have studied the 2L-VRP with stochastic customers under different loading configurations, while the investigations of the 2L-VRP with other uncertainties, such as stochastic demands, stochastic items and travel time, are yet to be carried out. Conceptualization, Z.Z. and B.J. ; methodology, Z.Z. and B.J. ; software, Z.Z. ; validation, Z.Z., B.J. and S.S.Y. ; formal analysis, B.J. and S.S.Y. ; resources, Z.Z. and B.J. ; writing--original draft preparation, Z.Z. ; writing--review and editing, Z.Z., B.J. and S.S.Y. ; visualization, Z.Z. and B.J. ; supervision, B.J. ; project administration, B.J. and S.S.Y. ; funding acquisition, B.J. and S.S.Y. All authors have read and agreed to the published version of the manuscript.