# Laureano F. EscuderoUniversidad Rey Juan Carlos Móstoles (Madrid) Spain

Laureano F. Escudero

PhD in Economic Sciences

Universidad Rey Juan Carlos, Research Fellow, Mostoles (Madrid), Spain

## About

257

Publications

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4,051

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Citations since 2016

Introduction

## Publications

Publications (257)

The hub location problem (HLP) basically consists of selecting nodes from a network to act as hubs to be used for flow traffic directioning, i.e., flow collection from some origin nodes, probably transfer it to other hubs, and distributing it to destination nodes. A potential expansion on the hub building and capacitated modules increasing along a...

Demand Side Management (DSM) is usually considered as a process of energy consumption shifting from peak hours to off-peak times. DSM does not always reduce total energy consumption, but it helps to meet energy demand and supply. For example, it balances variable generation from renewables (such as solar and wind) when energy demand differs from re...

Two matheuristic decomposition algorithms are introduced. The first one is a Progressive Hedging type so-named Regularized scenario Cluster Progressive Algorithm. The second one is a Frank-Wolfe PH type so-named Regularized scenario Cluster Simplicial Decomposition Progressive Algorithm. An extension of endogenous Type III uncertainty is considered...

This study focuses on the development of a mixed binary primal-dual bilinear model for multi-period bilevel network expansion planning under uncertainty, where pricing-based equilibrated strategic and operational decisions are to be made. The periodwise dependent parameters’ uncertainty is represented by a finite set of scenarios. Pricing-based equ...

A new scheme for dealing with the uncertainty in the scenario trees is considered in the presence of strategic and tactical stochastic parameters for a dynamic mixed 0–1 optimization model in a forest harvesting network along a time horizon under uncertainty. The strategic level of the model presented in this work is included by a several years tim...

A new scheme for dealing with uncertainty in scenario trees is presented for dynamic mixed 0–1 optimization problems with strategic and operational stochastic parameters. Let us generically name this type of problems as capacity expansion planning (CEP) in a given system, e.g., supply chain, production, rapid transit network, energy generation and...

In this work, the design and operation planning of a multi-period, multi-product closed-loop supply chain is addressed. Recovered end-of-life products from customers are evaluated in disassembly centers and accordingly are sent back to factories for remanufacturing, or leave the network either by being sold to third parties or by being sent to disp...

In this work we present two matheuristic procedures to build good feasible solutions (frequently, the optimal one) by considering the solutions of relaxed problems of large-sized instances of the multi-period stochastic pure 0–1 location-assignment problem. The first procedure is an iterative one for Lagrange multipliers updating based on a scenari...

A preparedness resource allocation model and an algorithmic approach are presented for a three-stage stochastic problem for managing natural disaster mitigation. That preparedness consists of warehouse location and capacity assignment and the procurement of commodities on the one hand and refurbishing the rescue network infrastructure on the other....

The Rapid Transit Network Design planning problem along a time horizon is treated by considering uncertainty in passenger demand, strategic costs and network disruption. The problem has strategic decisions about the timing to construct stations and edges, and operational decisions on the available network at the periods. The uncertainty in the stra...

A new time-consistent risk averse measure is considered, so-called Expected Conditional Stochastic Dominance (ECSD), for multistage stochastic mixed 0–1 optimization, where first- and second-order stochastic dominance risk averse functionals are taken into account. As a result of the ECSD modeling, its problem solving is much more difficult than th...

Rapid transit network design is highly dependent on the future system usage. These spatially distributed systems are vulnerable to disruptions: during daily operations different incidents may occur. Despite the unpredictable nature of them, effective mitigation methods from an engineering perspective should be designed. In this paper, we present se...

The paper presents and compares approaches for controlling forest companies' risk associated with advance planning under variable future timber prices and demand. Decisions to be made in advance are which stands to cut and which new access roads to build in each period, while maximizing profit under manageable risk. We first developed a tighter, im...

A 0-1 quadratic programming model is presented for solving the strategic problem of timing the location of facilities and the assignment of customers to facilities in a multi-period setting. It is assumed that all parameters are known and, on the other hand, the quadratic character of the objective function is due to considering the interaction cos...

In this work a modeling framework and a solution approach have been presented for a multi-period stochastic mixed 0-1 problem arising in tactical supply chain planning (TSCP). A multistage scenario tree based scheme is used to represent the parameters’ uncertainty and develop the related Deterministic Equivalent Model. A cost risk reduction is perf...

The aircraft conflict resolution problem needs to provide response to such situation in which two or more aircraft violate the safety distances that must be kept during the flight. Then, given the aircraft trajectories, the aim consists of finding a new configuration such that every conflict situation must be avoided. To deal with conflict avoidanc...

A parallel matheuristic algorithm is presented as a spin-off from the exact Branch-and-Fix Coordination (BFC) algorithm for solving multistage stochastic mixed 0-1 problems. Some steps to guarantee the solution’s optimality are relaxed in the BFC algorithm, such that an incomplete backward branching scheme is considered for solving large sized prob...

The conflict resolution problem in Air Traffic Management is tackled in this paper by using a mixed integer linear approximation to a Mixed Integer Nonlinear Optimization (MINO) model that we have presented elsewhere. The aim of the problem consists of providing a new aircraft configuration such that every conflict situation is avoided, a conflict...

Supply Chain Design problems often result into multiperiod stochastic mixed integer problems that are hard to solve. In this paper we propose a metaheuristic algorithm as a specialization for two- stage problems of the so-named Fix-and-Relax Algorithm presented previously for solving large- scale multiperiod stochastic mixed 0-1 optimization proble...

In this work we present an approach for designing the lines of a rapid transit network. Given the stations to be constructed and the links between them, a set of lines is generated by utilizing a greedy heuristic procedure that, taking into account the transfers that should be made by the users to arrive at their destinations, attempts to maximize...

This article concerns a multistate model with recurrent events, which are modeled by a discrete-time pure-birth process. The probability distribution of the lifetime of the multistate system is based on random sums with support on the natural numbers and with geometric summands, whose exact distribution is given in Belzunce et al. (2009) for indepe...

The aircraft Conflict Detection and Resolution (CDR) problem in air traffic management consists of finding a new configuration for a set of aircraft such that conflict situations between them are avoided. A conflict situation arises if two or more aircraft violate the safety distances that they must maintain in flight. In this paper we propose a Va...

In this work we present the sequential and parallel versions of a heuristic algorithm for the solution of a two-stage stochastic mixed 0-1 model for closed loop supply chain planning problem along a time horizon. Some computational experience conducted on randomly generated networks shows the quality of the proposed approach.

An exact mixed integer nonlinear optimization (MINO) model is presented for tackling the aircraft conflict detection and resolution problem in air traffic management. Given a set of flights and their configurations, the aim of the problem was to provide new configurations such that all conflict situations are avoided, with conflict situation unders...

We present a Lagrangean Decomposition approach for obtaining strong lower bounds on minimizing medium to large scale multistage stochastic mixed 0–1 problems. The problem is represented by a mixture of the splitting representation up to a given stage, so-named break stage, and the compact representation for the other stages along the time horizon....

We propose in this work a new multistage risk averse strategy based on Time Stochastic Dominance (TSD) along a given horizon. It can be considered as a mixture of the two risk averse measures based on first- and second-order stochastic dominance constraints induced by mixed integer-linear recourse, respectively. Given the dimensions of medium-sized...

A parallel computing implementation of a Serial Stochastic Dynamic Programming approach referred to as the S-SDP algorithm is introduced to solve large-scale multiperiod mixed 0-1 optimization problems under uncertainty. The paper presents Inner and Outer Parallelization versions of the S-SDP algorithm, referred to as Inner P-SDP and Outer P-SDP, r...

A mixed integer linear optimization model is presented for providing a cooperative system between Air Traffic Control Officers who manage the airspace for aircraft conflict detection and resolution. Elsewhere we have introduced the model for dealing with velocity and altitude changes in a given air sector. In this work, we extend the model to cover...

The aircraft conflict detection and resolution problem in air traffic management consists of deciding the best strategy for an arbitrary aircraft configuration such that all conflicts in the airspace are avoided. A conflict situation occurs if two or more aircraft do not maintain the minimum safety distance during their flight plans. A two-step app...

In this work we present the first stage of a two-stage approach for designing rapid transit networks, where the stations and links to be constructed are selected by solving an integer linear optimization model that maximizes an estimation of the number of trips through the rapid transit network. It is based on the first stage of another approach th...

Deterministic mine planning models along a time horizon have proved to be very effective in supporting decisions on sequencing the extraction of material in copper mines. Some of these models have been developed for, and used successfully by CODELCO, the Chilean state copper company. In this paper, we wish to consider the uncertainty in a very vola...

A multi-period discrete facility location problem is introduced for a risk neutral strategy with uncertainty in the costs and some of the requirements along the planning horizon. A compact 0-1 formulation for the Deterministic Equivalent Model of the problem under two alternative strategies for the location decisions is presented. Furthermore, a ne...

We present two-stage stochastic mixed 0---1 optimization models to hedge against uncertainty in production planning of typical small-scale Brazilian furniture plants under stochastic demands and setup times. The proposed models consider cutting and drilling ...

This paper studies a multistage stochastic programming (SP) model for large-scale network revenue management. We solve the model by means of the so-called expected future value (EFV) decomposition via scenario analysis, estimating the impact of the decisions made at a given stage on the objective function value related to the future stages. The EFV...

The Conflict Detection and Resolution Problem for Air Traffic Flow Management consists of deciding the best strategy for airborne
aircraft so that there is guarantee that no conflict takes place, i.e., all aircraft maintain the minimum safety distance
at every time instant. Two integer linear optimization models for conflict avoidance between any n...

We propose a two-stage stochastic optimization model for maximizing the profit of a price-taker power producer who has to decide his own power generation capacity expansion plan in a long time horizon, taking into account the uncertainty of the following parameters: fuel costs; market electricity prices, as well as prices of green certificates and...

Two-dimensional strip packing problem is to pack given rectangular pieces on a strip of stock sheet having fixed width and infinite height. Its aim is to minimize the height of the strip such that non-guillotinable and fix orientation constraints are ...

In this paper we introduce four scenario Cluster based Lagrangian Decomposition procedures for obtaining strong lower bounds to the (optimal) solution value of two-stage stochastic mixed 0–1 problems. At each iteration of the Lagrangian based procedures, the traditional aim consists of obtaining the solution value of the corresponding Lagrangian du...

In this paper we present a set of approaches for stochastic optimizing of immunization strategies based on risk averse measures as alternatives to the optimization of the objective function expected value, i.e., in the so-called risk neutral environment. The risk averse measures to consider whose validity is analyzed in this work are as follows: tw...

The Vertex Separation Problem belongs to a family of optimization problems in which the objective is to find the best separator of vertices or edges in a generic graph. This optimization problem is strongly related to other well-known graph problems; such as the Path-Width, the Node Search Number or the Interval Thickness, among others. All of thes...

A mixed 0–1 nonlinear high nonconvex model is presented for solving the collision avoidance problem in Air Traffic Management. The aim is to give a new configuration for a set of aircraft such that their conflict situations are avoided. A conflict situation happens if two or more aircraft violate the safety distances that they have to keep during t...

In this paper a mixed 0-1 nonlinear model for the Collision Avoidance problem in Air Traffic Management is presented. The aim of the problem consists of deciding the best strategy for an arbitrary aircraft configuration such that all conflicts in the airspace are avoided where a conflict is the loss of the minimum safety distance that two aircraft...

A multi-period stochastic model and an algorithmic approach to location of prison facilities under uncertainty are presented and applied to the Chilean prison system. The problem consists of finding locations and sizes of a preset number of new jails and determining where and when to increase the capacity of both new and existing facilities over a...

In this paper we present a set of approaches for stochastic optimizing of immunization strategies based on risk averse measures as alternatives to the optimization of the objective function expected value, i.e., in the so-called risk neutral environment. The risk averse measures to consider whose validity is analyzed in this work are as follows: tw...

In this paper a deterministic mixed 0-1 model for the air traffic flow management problem is presented. The model allows for flight cancelation and rerouting, if necessary. It considers several types of objective functions to minimize, namely, the number of flights exceeding a given time delay (that can be zero), separable and non-separable ground...

We present a framework for modeling multistage mixed 0-1 problems for the air traffic flow management problem with rerouting (ATFMRP) under uncertainty in the airport arrival and departure capacity, the air sector capacity and the flight demand. The model allows for flight cancelation, if necessary. It considers several types of objective functions...

In this paper we present a parallelizable Branch-and-Fix Coordination algorithm for solving medium and large-scale multistage mixed 0–1 optimization problems under uncertainty. The uncertainty is represented via a nonsymmetric scenario tree. An information structuring for scenario cluster partitioning of nonsymmetric scenario trees is also presente...

Many rule systems generated from decision trees (like CART, ID3, C4.5, etc.) or from direct counting frequency methods (like Apriori) are usually non-significant or even contradictory. Nevertheless, most papers on this subject demonstrate that important reductions can be made to generate rule sets by searching and removing redundancies and conflict...

In this paper, we present a binary integer linear program for obtaining the optimal combination of gears to install on a competitive racing motorcycle. Our objective is to meet the requirements of both the rider and track at a set of points on the racing circuit. This requires determining the best transmission (gearbox) for each circuit and rider....

In this paper we introduce four scenario Cluster based Lagrangian Decomposition (CLD) procedures for obtaining strong lower bounds to the (optimal) solution value of two-stage stochastic mixed 0-1 problems. At each iteration of the Lagrangian based procedures, the traditional aim consists of obtaining the solution value of the corresponding Lagrang...

The optimization of stochastic linear problems, via scenario analysis, based on Benders decomposition requires appending feasibility and/or optimality cuts to the master problem until the iterative procedure reaches the optimal solution. The cuts are identified by solving the auxiliary submodels attached to the scenarios. In this work, we propose t...

The forest harvest and road construction planning problem consists fundamentally of managing land designated for timber production
and divided into harvest cells. For each time period the planner must decide which cells to cut and what access roads to build
in order to maximize expected net profit. We have previously developed deterministic mixed i...

In this paper we introduce some improvements on an approach that we described elsewhere
for solving a modification of the well-known extended rapid transit network design
problem. Firstly, we propose an integer programming model for selecting the stations to be
constructed and the links between them, in such a way that a connected rapid transit
net...

In this note we present the basic ideas of a parallelizable Branch-and-
Fix Coordination algorithm for solving medium and large-scale multistage mixed
0-1 optimization problems under uncertainty, where this one is represented by nonsymmetric
scenario trees. An assignment of the constraint matrix blocks into independent
scenario cluster MIP submodel...

A multistage complete recourse model for structuring energy contract portfolios in competitive markets is presented for price-taker
operators. The main uncertain parameters are spot price, exogenous water inflow to the hydro system and fuel-oil and gas cost.
A mean-risk objective function is considered as a composite function of the expected tradin...

In this paper a stochastic version of the set packing problem (SPP), is studied via scenario analysis. We consider a one-stage recourse approach to deal with the uncertainty in the coefficients. It consists of maximizing in the stochastic SPP a composite function of the expected value minus the weighted risk of obtaining a scenario whose objective...

We present a Branch and Fix Coordination algorithm for solving
medium and large scale multi-stage mixed 0-1 & combinatorial
optimization problems under uncertainty. The uncertainty is represented
via a nonsymmetric scenario tree. The basic idea consists
of explicitly rewriting the nonanticipativity constraints (NAC)
of the 0-1 and continuous variab...

In this paper we introduce a scenario cluster based Lagrangean Decomposition
(LD) scheme for obtaining strong lower bounds to the
optimal solution of two-stage stochastic mixed 0-1 problems. At
each iteration of the Lagrangean based procedures, the traditional
aim consists of obtaining the optimal solution value of the corresponding
Lagrangean dual...

This paper tackles the collision-avoidance problem in air traffic management. The problem consists of deciding the best strategy for new aircraft configurations (velocity and altitude changes) such that all conflicts in the airspace, i.e., the loss of the minimum safety distance that has to be kept between two aircraft, are avoided. A mixed 0-1 lin...

This paper tackles the collision avoidance problem in ATM. The problem consists in deciding the best strategy for new aircraft configurations (velocity and altitude changes) such that all conflicts in the airspace are avoided; a conflict being the loss of the minimum safety distance that has to be kept between two aircrafts. A mixed 0-1 linear opti...

Preprint submitted to Computers & Operations Research

In this paper we present the models and the algorithms which are being used in a decision support system (DSS) to determine water irrigation scheduling. The DSS provides dynamic scheduling of the daily irrigation for a given land area by taking into account the irrigation network topology, the water volume technical conditions and the logistical op...