Summary
In the maximum cardinality bin packing problem (MCBPP), we have n items with different sizes and m bins with the same capacity. We want to assign a maximum number of items to the fixed number of bins without violating the capacity constraint on each bin. We develop a heuristic algorithm for solving the MCBPP that is based on weight annealing. Weight annealing is a metaheuristic that has been recently proposed in the physics literature. We apply our algorithm to two data sets containing 4,500 randomly generated instances and show that it outperforms an enumeration algorithm and a branch-and-price algorithm.
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Loh, KH., Golden, B., Wasil, E. (2009). Solving the Maximum Cardinality Bin Packing Problem with a Weight Annealing-Based Algorithm. In: Chinneck, J.W., Kristjansson, B., Saltzman, M.J. (eds) Operations Research and Cyber-Infrastructure. Operations Research/Computer Science Interfaces, vol 47. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-88843-9_8
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DOI: https://doi.org/10.1007/978-0-387-88843-9_8
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