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Online 3-dimensional bin packing problem (O3D-BPP) is getting renewedprominence due to the industrial automation brought by Industry 4.0. However,due to limited attention in the past and its challenging nature, a goodapproximate algorithm is in scarcity as compared to 1D or 2D problems. Thispaper considers real-time O$3$D-BPP of cuboidal boxes with partial information(look-ahead) in an automated robotic sorting center. We present tworolling-horizon mixed-integer linear programming (MILP) cum-heuristic basedalgorithms: MPack (for bench-marking) and MPackLite (for real-time deployment).Additionally, we present a framework OPack that adapts and improves theperformance of BP heuristics by utilizing information in an online setting witha look-ahead. We then perform a comparative analysis of BP heuristics (with andwithout OPack), MPack, and MPackLite on synthetic and industry provided datawith increasing look-ahead. MPackLite and the baseline heuristics performwithin bounds of robot operations and thus, can be used in real-time.

A generalized algorithm and framework for online 3-dimensional bin packing in an automated sorting center