Abstract
Group buying is attracting a lot of attention, but studies on group buying of bundled products are still in their infancy. In this study, a group purchasing structure is proposed in which each purchaser needs a portion of the items in a bundle and has his or her preferences. However, when the buyers of a bundle are scattered across different locations, the shipper must travel long distances between buyers, which increases shipping costs. Therefore, besides bundle prices, shipping costs are an inseparable expenditure for group purchasing. It is assumed that shipping costs increase on certain days, e.g. around Christmas. A tailored mathematical formulation is formulated to maximize the total group saving. Considering the complexity of the model, a genetic algorithm (GA) is developed as a solution algorithm, and compared with the CPLEX solver. The results confirm the performance of the GA, which provides up to 24% better solutions than CPLEX.
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