The literature reviewed in Table 2 reveals the use of various heuristic methods and meta-heuristics to address the container-loading problem, including PSO, GA, ABC, ACO, DE, and hybrid methods. Notably, some studies proposed unique approaches, such as a multi-population biased random-key genetic algorithm (BRKGA) or an ant colony stacking method (ASM). However, a gap remains in the literature on combining artificial bee colony algorithms with a Pareto-based approach to tackle this problem. Thus, this research introduces the artificial bee colony algorithm with the Pareto-based approach. To our knowledge, this is the first study to present the aforementioned method to simultaneously maximize profit and space utilization for a single container of fixed size. In summary, the reviewed literature suggests a lack of research exploring the effectiveness of box rotation techniques in optimizing the multi-objective 3D container-loading problem. There is a need for research to investigate the use of combining artificial bee colony algorithms with a Pareto-based approach to tackle a multi-objective problem. Additionally, the proposed bottom-left fill with rotation heuristic algorithm incorporating a hybrid method is the first method to propose simultaneously maximizing profit and space utilization for a single container with fixed dimensions. Thus, in this research, we combine the artificial bee colony algorithm with a Pareto-based approach to solve the SCLP for strongly heterogeneous rectangular boxes. The ABC algorithm is commonly used by researchers because of its simplicity, flexibility, robustness, ability to explore local solutions, ability to handle objective costs, and broad applicability with complex functions [31]. However, one of its well-known limitations is its tendency to get trapped in local optima, which is ascribed to its exploration process. The proposed algorithm avoids this issue by utilizing a powerful meta-heuristics approach with a Pareto \begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Author and Year**} & \multirow{2}{*}{**Topic Research**} & \multirow{2}{*}{**Problem**} & \multicolumn{3}{c}{**The Dimension**} & \multicolumn{3}{c}{**Objective**} & \multirow{2}{*}{**Rotations**} \\ \cline{5-10}  & & & & **1D** & **2D** & **3D** & **Single** & **Multi** & **Rotate** & **No** \\ \hline [PERSON] et al., 2016 [15] & An effective placement method for the single-container-loading problem & Single-container-loading problem & - & ✓ & - & ✓ & - & - & ✓ \\ \hline [PERSON] et al., 2017 [16] & VCS: a new heuristic function for selecting boxes in the single-container-loading problem & Single-container-loading problem & - & ✓ & - & ✓ & - & - & ✓ \\ \hline [PERSON] et al., 2021 [17] & Novel binary differential evolution algorithm for knapsack problems & Knapsack problem & ✓ & - & - & ✓ & - & - & ✓ \\ \hline [PERSON] et al., 2021 [18] & A binary equilibrium optimization algorithm for the 0-1 knapsack problem & Knapsack problem & ✓ & - & - & ✓ & - & - & ✓ \\ \hline [PERSON] et al., 2022 [19] & GWO-based simulated annealing approach for load balancing in the cloud for hosting containers as a service & Load balancing in the containerized cloud & - & - & ✓ & ✓ & - & - & ✓ \\ \hline [PERSON] et al., 2022 [20] & Solving the integrated multi-port storage planning and container relocation problems with a genetic algorithm and simulation & Container relocation problem & - & - & ✓ & ✓ & - & - & ✓ \\ \hline [PERSON] et al., 2023 [21] & Multi-objective scheduling strategy of mine transportation robot based on three-dimensional loading constraints & Multiple-container-loading problem & - & - & ✓ & - & ✓ & - & ✓ \\ \hline \multirow{3}{*}{This paper} & Artificial bee colony algorithm with & & & & & & & & \\ \cline{1-1}  & pareto-based approach for multi-objective three-dimensional single-container-loading problems & Single-container-loading problem & - & - & ✓ & - & ✓ & ✓ & - \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Literature relevant to the knapsack problem and container-loading problem.