Heuristic Generation via Parameter Tuning for Online Bin Packing

Online bin packing requires immediate decisions to be made 14 placing an incoming item one at a time into bins of fixed capacity without causing any overflow. The goal is to maximise the average bin fullness after placement of a long stream of items. A recent work describes an approach for solving this problem based on a 'policy matrix' representation in which each decision option is independently given a value and the highest value option is selected. A policy matrix can also he viewed as a heuristic with many parameters and then the search for a good policy matrix can he treated as a parameter tuning process. In this study, we show that the trace parameter tuning algorithm produces heuristics which outperform the standard human designed heuristics for various instances of the online bin packing problem.