One-Dimensional Bin Packing Problem: An Experimental Study of Instances Difficulty and Algorithms Performance

AbstractThe one-dimensional Bin Packing Problem (BPP) is one of the best-known optimization problems, and it has a significant number of applications. For this reason, several strategies have been proposed to solve it, but only few works have focused on the study of the characteristics that distinguish the BPP instances and that could affect the performance of the algorithms that solve it. In this work, we present a comprehensive study of the performance of four well-known algorithms on a set of new BPP instances. First, the features of the instances and the performance of the algorithms are quantified by indices; next, an exploratory analysis of the indices is carried out in order to identify the characteristics that define the difficulty of a BPP instance and to understand the performance of the algorithms. The algorithmic behavior explanations obtained by the study suggest that the difficulty of the BPP instances is related to: (1) the bin capacity; (2) the dispersion of the items weights; and (3) the difference between the largest and the smallest items weight.KeywordsBin packingInstance difficultyAlgorithmic performanceCharacterization