### The State-of-the-Art Design of Palletized Load Units  
In the literature, the problem of planning pallet load units is called _bin packing problem_--_BPP_. To solve the problem, one needs to define which items of different sizes need to be packed into a finite number of bins or containers, each of a given and fixed capacity so as to minimize the number of bins used. In the literature, the same problem, depending on the authors, is referred to as pallet loading problem--PLP, e.g., [PERSON] and [PERSON] [2], [PERSON] et al. [3], pallet building problem--PBP, e.g., [PERSON] et al. [4], container loading problem--CLP, e.g., [PERSON] and [PERSON] [5], or packing problem--PP, e.g., [PERSON] et al. [6]. Since the packing problem is an NP-hard decision problem, it can also be analyzed, with the exception of its principal constraint, i.e., the weight of the product, as a soft version of two dimensions (2D), i.e., width x length of the products to be packed, e.g., [PERSON] and [PERSON] [7], or a more complex problem of three dimensions (3D), i.e., width x length x height, e.g., [PERSON] and [PERSON] [1], [PERSON] et al. [3], or [PERSON] et al. [6]. From the perspective of the location, the packing problem is analyzed and planned with respect to homogenous items by some of the researchers who refer to it as manufacturer's pallet loading--MPL, e.g., [PERSON] et al. [3]. When packaging involves heterogeneous items, it is called distributor's pallet loading--DPL; see [PERSON] et al. [8]. In general, the bin packing problem can be analyzed as a stand-alone packing problem or as a part of a more complex problem, i.e., in combination with vehicle loading. As far as the stand-alone approach is concerned, it has been extensively analyzed as a decision problem for around 50 years. In recent years several papers have been published to review or compare different approaches to this problem [6; 9]. [PERSON] et al. [9] reviewed the papers with respect to the methods proposed for the solution of the problem. In conclusion, a group of the most challenging methods was identified. [PERSON] et al. [6] analyzed different approaches to the decision-making problem concerning packing. They differentiated 3D off-line vs. on-line streams of packing problems. Off-line packing problems can happen when full knowledge about items is available beforehand. The on-line problem, i.e., real-time problem, is when items arrive one by one, and the packing decision should be made immediately without prior knowledge about the items. According to [PERSON] et al., most of the packing problems described in the literature are of the off-line type. Contemporary examples of the on-line bin packing problem can be found in [PERSON] et al. [10], where a pattern-based adaptive heuristics for the on-line bin packing problem is proposed. The distribution of items may be predicted based on the packed items, and the pattern is next applied in the packing of the items that arrive later. Some new research into the bin packing problem was published in the last few years. [PERSON] et al. [11] analyzed a wide spectrum of practical constraints, including vertical support, load bearing, planogram sequencing, and weight limits. The authors performed extensive numerical tests to prove the ability of the approach to find high-quality solutions for industrial-size instances within a short computational time. There are also some recent papers on the application of more efficient computational procedures whose aim is to achieve computation results in the shortest time possible. [PERSON] et al. [12] published a paper on the 3D bin packing problem (3D-BPP) where they proposed a model oriented on pallets configurations to satisfy the practical requirements of item grouping by logistic features such as load bearing, stability, height homogeneity, overhang as well as weight limits, and robotized layer picking. The complex problem is solved with metaheuristics, which combines MILP formulation and layer-building heuristics. Moreover, 3D-BPP is analyzed in the work of [PERSON] et al. [13].