arXiv subjects

Laureano F. Escudero

Publications and source records attributed to Laureano F. Escudero.

3 recordsLinked to original sources

arXiv2026

Cross-Dock Door Design under Uncertainty: A two-stage DRO-based lower- and upper-bounding scheme

The stochastic cross-dock door design problem entails determining the number of doors and their nominal capacities under uncertainty. The inbound flow of commodities from origin nodes is assigned to the entry doors consolidated in the platform, and the outbound flow is assigned to the exit doors to be delivered to the destination nodes. This problem combines three high computational difficulties, namely, NP-hard quadratic combinatorics, uncertainty in the main parameters, and ambiguity in their probability distribution. Distributionally robust optimization is considered to deal with these uncertainties. A two-stage mixed binary quadratic model is presented, where the first stage decisions are related to the design of the platform and the second stage ones are related to the assignment of the commodity flow to the doors in the members of the ambiguity set. The goal is to minimize the highest total cost in the ambiguity set, subject to the constraint system for each of those members. In addition to the risk-neutral version, a risk-averse formulation is presented. Given the difficulty of this problem, a min-max matheuristic scheme based on a scenario cluster decomposition is proposed for obtaining lower and upper bounds. A computational study is conducted to compare the solutions provided by the straightforward use of the state-of-the-art solvers CPLEX and Gurobi, as well as to validate the proposed matheuristic scheme.

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arXiv2026

Multi-horizon optimization for domestic renewable energy system design under uncertainty

In this paper we address the challenge of designing optimal domestic renewable energy systems under multiple sources of uncertainty appearing at different time scales. Long-term uncertainties, such as investment and maintenance costs of different technologies, are combined with short-term uncertainties, including solar radiation, electricity prices, and uncontrolled load variations. We formulate the problem as a multistage multi-horizon stochastic Mixed Integer Linear Programming (MILP) model, minimizing the total cost of a domestic building complex's energy system. The model integrates long-term investment decisions, such as the capacity of photovoltaic panels and battery energy storage systems, with short-term operational decisions, including energy dispatch, grid exchanges, and load supply. To ensure robust operation under extreme scenarios, first- and second-order stochastic dominance risk-averse measures are considered preserving the time consistency of the solution. Given the computational complexity of solving the stochastic MILP for large instances, a rolling horizon-based matheuristic algorithm is developed. Additionally, various lower-bound strategies are explored, including wait-and-see schemes, expected value approximations, multistage grouping and clustering schemes. An extensive computational experiment validates the effectiveness of the proposed approach on a case study based on a building complex in South Germany. We tackle models with over 43 million constraints and 12 million binary, 700 hundred integer and 10 million continuous variables; they are solved with up to 0.32% optimality gap in reasonable computing time, where the value of the stochastic decisions as well as the benefit of the integrated risk-averse measures are quantified.

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arXiv2024

A methodology for the cross-dock door platforms design under uncertainty

The cross dock door design problem consists of deciding on the number and capacity of inbound and outbound doors for receiving product pallets from origin nodes and exiting them to destination nodes. The uncertainty, realized in scenarios, lies in the occurrence of these nodes, the number and cost of the pallets, and the disruption of the capacity of the doors. It is represented using a stochastic two stage binary quadratic model. The first stage decisions are related to the cross dock infrastructure design, and the second stage decisions are related to the node to assignments of the doors. This is the first time, as far as we know, that a stochastic two stage binary quadratic model has been presented for minimizing the construction cost of the infrastructure and its exploitation expected cost in the scenarios. Given the difficulty of solving this combinatorial problem, a mathematically equivalent mixed integer linear formulation is introduced. However, searching an optimal solution is still impractical for commercial solvers. Thus, a scenario cluster decomposition based matheuristic algorithm is introduced to obtain feasible solutions with small optimality gap and reasonable computational effort. A broad study to validate the proposal gives solutions with a much smaller gap than the ones provided by a state of the art general solver. In fact, the proposal provides solutions with a 1 to 5% optimality gap, while the solver does it with up to a 12% gap, if any, and requires a wall time two orders of magnitude higher.

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