In this paper, a benchmark for real-world bin packing problems is proposed. This dataset is composed of 12 instances comprehending different levels of problem complexity regarding size (with the number of packages ranging from 38 to 53) and user-defined requirements. In fact, several real-world oriented restrictions have been considered for building these instances: i) items and bins dimensions, ii) weight restrictions, iii) affinities among packages categories iv) preferences for package ordering and v) load balancing. Besides the data, we also provide an own-developed Python script for the dataset generation, coined as Q4RealBPP-DataGen. The benchmark was firstly proposed to evaluate quantum solvers, therefore the characteristic of this set of instances were designed according to the current limitations of quantum devices. Additionally, the dataset generator is included to allow the construction of general-purpose benchmarks. The data introduced on this paper provides a baseline that will encourage quantum computing researchers to work on real-world bin packing problems
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