The Generalized Bin Packing Problem under Uncertainty
نویسندگان
چکیده
In this paper we introduce the Generalized Bin Packing Problem under Uncertainty, a new packing problem where, given a set of items characterized by volume and stochastic revenue and a set of bins characterized by volume and cost, we want to select a subset of items to be loaded into a subset of bins which maximizes the total profit, given by the difference between the expected total revenue of the loaded items and the total cost of the used bins, by satisfying the volume and bin availability constraints. The item revenues are random variables with unknown probability distribution. By using the asymptotic theory of extreme values a nonlinear integer deterministic model is derived. Key-Words: packing, stochastic revenue, asymptotic approximation, nonlinear integer deterministic model.
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