Solving Discrete Ordered Median Problems with Induced Order

Ordered median functions have been developed to model flexible discrete location problems. A weight is associated to the distance from a customer to its closest facility, depending on the position of that distance relative to the distances of all the customers. In this paper, the above idea is extended by adding a second type of facility and, consequently, a second weight, whose values are based on the position of the first weights. An integer programming formulation is provided in this work for solving this kind of models

On green routing and scheduling problem

The vehicle routing and scheduling problem has been studied with much interest within the last four decades. In this paper, some of the existing literature dealing with routing and scheduling problems with environmental issues is reviewed, and a description is provided of the problems that have been investigated and how they are treated using combinatorial optimization tools

Intra-facility equity in discrete and continuous p-facility location problems

We consider facility location problems with a new form of equity criterion. Demand points have preference order on the sites where the plants can be located. The goal is to find the location of the facilities minimizing the envy felt by the demand points with respect to the rest of the demand points allocated to the same plant. After defining this new envy criterion and the general framework based on it, we provide formulations that model this approach in both the discrete and the continuous framework. The problems are illustrated with examples and the computational tests reported show the potential and limits of each formulation on several types of instances. Although this article is mainly focused on the introduction, modeling and formulation of this new concept of envy, some improvements for all the formulations presented are developed, obtaining in some cases better solution times.Project TED2021-130875B-I00, supported by MCIN/AEI/ 10.13039/ 501100011033 and the European Union ‘‘NextGenerationEU/PRTR’’Research project PID2022- 137818OB-I00 (Ministerio de Ciencia e Innovación, Spain)Agencia Estatal de Investigación (AEI), Spain: PID2020-114594GB-C2; Regional Government of Andalusia, Spain P18-FR-1422 and B-FQM-322-UGR20 (ERDFIMAG-Maria de Maeztu, Spain grant CEX2020-001105-M/AEI/10.13039/ 501100011033Funding for open access charge: Universidad de Granada / CBU

Balancing the arrival times of users in a two-stage location problem

There has been a number of facility location problems dealing with the introduction of the equity issue in the travel distances distribution. In this paper we analyze a new aspect of equity concerning the distribution of the arrival times of customers. Given a depot and a set of demand points generating flow which also represent potential locations, we consider a discrete two-stage location problem whose aim is to locate a given number of facilities and to allocate the demand points to a facility. We assume as objective the maximization of the minimum difference between two consecutive arrival times of flows to the depot through the patronized facility. This particular equity measure is introduced in order to reduce risks of congestion in the dynamic of flow arrivals at the common destination. The problem is described through two Integer Programming formulations. Computational results for solution methods based on both formulations are then shown and analyzed

Fairness in maximal covering location problems

Acknowledgments The authors thank the anonymous reviewers and the guest editors of this issue for their detailed comments on this paper, which provided significant insights for improving the previous versions of this manuscript. This research has been partially supported by Spanish Ministerio de Ciencia e Innovación, AEI/FEDER grant number PID2020-114594GB C21, AEI grant number RED2022-134149-T (Thematic Network: Location Science and Related Problems), Junta de Andalucía projects P18- FR-1422/2369 and projects FEDERUS-1256951, B-FQM-322-UGR20, CEI-3-FQM331 and NetmeetData (Fundación BBVA 2019). The first author was also partially supported by the IMAG-Maria de Maeztu grant CEX2020-001105-M /AEI /10.13039/501100011033 and UENextGenerationEU (ayudas de movilidad para la recualificación del profesorado universitario. The second author was also partially supported by the Research Program for Young Talented Researchers of the University of Málaga under Project B1-2022_37, Spanish Ministry of Education and Science grant number PEJ2018-002962-A, and the PhD Program in Mathematics at the Universidad de Granada.This paper provides a mathematical optimization framework to incorporate fairness measures from the facilities’ perspective to discrete and continuous maximal covering location problems. The main ingredients to construct a function measuring fairness in this problem are the use of (1) ordered weighted averaging operators, a popular family of aggregation criteria for solving multiobjective combinatorial optimization problems; and (2) -fairness operators which allow generalizing most of the equity measures. A general mathematical optimization model is derived which captures the notion of fairness in maximal covering location problems. The models are first formulated as mixed integer non-linear optimization problems for both the discrete and the continuous location spaces. Suitable mixed integer second order cone optimization reformulations are derived using geometric properties of the problem. Finally, the paper concludes with the results obtained from an extensive battery of computational experiments on real datasets. The obtained results support the convenience of the proposed approach.Spanish Ministerio de Ciencia e InnovaciónAEI/FEDER grant number PID2020-114594GB C21AEI grant number RED2022-134149-T (Thematic Network: Location Science and Related Problems)Junta de Andalucía projects P18- FR-1422/2369FEDERUS-1256951B-FQM-322-UGR20CEI-3-FQM331NetmeetData (Fundación BBVA 2019)IMAG-Maria de Maeztu grant CEX2020-001105-M /AEI /10.13039/501100011033UE NextGenerationEUResearch Program for Young Talented Researchers of the University of Málaga under Project B1-2022_37Spanish Ministry of Education and Science grant number PEJ2018-002962-

Methods and Tools for the Microsimulation and Forecasting of Household Expenditure

This paper reviews potential methods and tools for the microsimulation and forecasting of household expenditure. It begins with a discussion of a range of approaches to the forecasting of household populations via agent-based modelling tools. Then it evaluates approaches to the modelling of household expenditure. A prototype implementation is described and the paper concludes with an outline of an approach to be pursued in future work

Methods and Tools for the Microsimulation and Forecasting of Household Expenditure - A Review

This paper reviews potential methods and tools for the microsimulation and forecasting of household expenditure. It begins with a discussion of a range of approaches to the forecasting of household populations via agent-based modelling tools. Then it evaluates approaches to the modelling of household expenditure. A prototype implementation is described and the paper concludes with an outline of an approach to be pursued in future work

FDI and Taxation: A Meta-Study

Despite the continuing political interest in the usefulness of tax competition and tax coordination as well as the wealth of theoretical analyses, it still remains open whether or when tax competition is harmful. Moreover, the influence of tax differentials on multinationals’ decisions is still insufficiently analyzed. Thus, economists have increasingly resorted to empirical analysis in order to gain insights on the elasticity of FDI with respect to company taxation. As a result, the empirical literature on taxation and international capital flows has grown to a similar abundance during the last 25 years as the respective theoretical literature. Its heterogeneity leads to a rising need for concise reviews on the existing empirical evidence. In this paper we extend former meta-analyses on FDI and taxation in three ways. First, we add the most recent publications unconsidered in meta-analyses up-to-date. Second, we apply a different methodology by using a broad set of meta-regression estimators and explicitly discuss which one is most suitable for application to our meta-data. Third, we address some important issues in research on FDI and taxation to the clarification of which meta-analysis can make valuable contributions. These issues are mainly: The influence of variables which might moderate effects of tax differentials (e.g. public spending), the implications of using aggregate FDI data as opposed to firm-level information on measured tax effects, the implications of bilateral effective tax rates, and the possible presence of publication bias in primary research.corporate income taxation, foreign direct investment, meta analysis