Two-stage Distributionally Robust Optimization for Cross-dock Door Design
The cross-dock door design problem consists of deciding the strip and stack doors and nominal capacity of an entity under uncertainty. Inbound commodity flow from origin nodes is assigned to the strip doors, it is consolidated in the entity, and the outbound flow is assigned to the stack ones for be...
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Main Authors | , , |
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Format | Journal Article |
Language | English |
Published |
02.06.2025
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Subjects | |
Online Access | Get full text |
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Summary: | The cross-dock door design problem consists of deciding the strip and stack
doors and nominal capacity of an entity under uncertainty. Inbound commodity
flow from origin nodes is assigned to the strip doors, it is consolidated in
the entity, and the outbound flow is assigned to the stack ones for being
delivered to destination nodes, at a minimum cost. The problem combines three
highly computational difficulties, namely, NP-hard combinatorics, uncertainty
in the main parameters and their probability distribution. Distributionally
robust optimization is considered to deal with these uncertainties. Its related
two-stage mixed binary quadratic model is presented for cross-dock
problem-solving; the first stage decisions are related to the design of the
entity; the second stage ones are related to the assignment of the commodity
flow to the doors in a finite set of scenarios for the ambiguity set members.
The goal is to minimize the highest total cost in the ambiguity set, subject to
the constraint system for each of those members and the stochastic dominance
risk averse functional. As far as we know, the challenging problem that results
has not been addressed before, although its application field is a very broad
one. Given the problem-solving difficulty, a scenario cluster decomposition and
a min-max based matheuristic are proposed for obtaining lower and upper bounds,
respectively. A computational study validates the proposal; it overperformances
the straightforward use of the state-of-the-art solvers Cplex and Gurobi. |
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DOI: | 10.48550/arxiv.2506.01694 |