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    Item type:Publication,
    The latency location routing problem with split deliveries: mathematical formulation and metaheuristic algorithm
    (2024) ;
    José Emmanuel Gómez‐Rocha
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    José‐Fernando Camacho‐Vallejo
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    Javier A. Moraga Pardo
    ;
    Rosa G. González‐Ramírez
    <jats:title>Abstract</jats:title><jats:p>Integrating location and routing into a unified decision‐making framework offers a more comprehensive reflection of real‐world scenarios where different facility layouts directly influence routing plans. Consequently, addressing the issue holistically becomes imperative, especially when considering service level metrics like customer waiting times. In this paper, we address the latency location routing problem with opening costs and split deliveries (LLRP‐OCSD). This complex problem involves optimizing the design of a supply chain network by determining depot locations, assigning vehicles and demand nodes to these depots, and designing routes. This must be done while accommodating split deliveries and prioritizing minimizing waiting times for demand nodes. We formulate a mathematical model and propose an iterated local search (ILS) algorithm to solve the problem. To validate the performance of our approach, we adapted a set of benchmark instances previously used for LLRP‐OC without considering split deliveries. Computational results demonstrate that the proposed model is able to optimally solve only 2 out of the 38 tested instances within a 2‐hour timeframe. On the other hand, the proposed ILS algorithm is able to find good‐quality solutions in significantly less computational time for the LLRP‐OCSD. Extensive experimentation on larger instances (up to 200 nodes) yields consistent results within reasonable computational limits. In summary, our findings highlight how split deliveries enhance vehicle utilization, enabling the use of smaller vehicles and creating balanced routes with minimal increases in latency costs.</jats:p>
      5
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    Scopus© Citations 3  1  26
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    Scopus© Citations 27  1  27
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    Predicting Postpartum Depression in Maternal Health Using Machine Learning
    (SCITEPRESS - Science and Technology Publications, 2025)
    Terreros Lozano, María Alejandra
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    Diana Lopez-Soto
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    María López-Ceballos
      21
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    Item type:Publication,
    A matheuristic augmented ɛ-constraint framework for a bi-objective Multi-Depot Cumulative Capacitated Vehicle Routing Problem
    (Elsevier BV, 2026-06)
    Segredo, Eduardo
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    Miranda, Gara
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    Lalla-Ruiz, Eduardo
    In this work, we extend the Multi-Depot Cumulative Capacitated Vehicle Routing Problem (MDCCVRP) to consider two objectives. Besides its cumulative aspect, i.e., minimizing the sum of customers’ waiting time, we also consider the travel cost minimization. To tackle this problem, we propose a novel matheuristic framework, called Math-AUGMECON-II, consisting of two stages. In the first stage, a multiobjective memetic algorithm based on the well-known Non-dominated Sorting Genetic Algorithm II (NSGA-II) is used to obtain an approximation to the Pareto front. This approximation of the Pareto front is then optimized in a second stage using the Augmented ɛ-Constraint II (AUGMECON-II) approach. The performance of NSGA-II, AUGMECON-II, and Math-AUGMECON-II is evaluated by their application to a set of well-known instances of the MDCCVRP with different sizes. The analyses based on different metrics, such as the number of solutions, hypervolume, and set coverage, reveal that AUGMECON-II is a suitable choice for small instances, while Math-AUGMECON-II is more appropriate to deal with medium and large instances, including instances with a reduced fleet size. Finally, a trade-off evaluation was carried out to examine the extent to which enhancing one objective impacts the other. It revealed that improving latency leads to an increase in travel cost, while improving travel cost results in a deterioration of latency. This highlights the asymmetric compromise between both objectives. © 2026 The Authors
      1
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    A Capacitated Vehicle Routing Model for Distribution and Repair with a Service Center
    <jats:p>Background: Distribution systems often face the dual challenge of delivering products to customers and retrieving damaged items for repair, especially when the service center is separate from the depot. An optimized solution to this logistics problem produces benefits in terms of costs, greenhouse gas emissions, and disposal reduction. Methods: This research proposes a Capacitated Vehicle Routing Problem with Service Center (CVRPwSC) model to determine optimal routes involving customers, the depot, and the service center. AMPL-Gurobi was used to solve the model on adapted instances and new instances developed for the CVRPwSC. Additionally, a Variable Neighborhood Search (VNS) algorithm was implemented and compared with AMPL-Gurobi. Results: The model was applied to a real-world case study, achieving a 40% reduction in fuel costs, a reduction from 5 to 3 routes, and a sustainable logistics operations model with potential reductions of greenhouse gas emissions and item disposals. Conclusions: The main contribution of the proposal is a minimum-cost routing model integrating item returns for repair with customer deliveries, while the limitation is the exclusion of scenarios where return items exceed vehicle capacity. Finally, future research will enhance the CVRPwSC model by incorporating additional constraints and decision variables to address such scenarios.</jats:p>
      18
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    Systematic Review of Literature on Lean and Six Sigma in Healthcare and Directions for Future Research
    (IEOM Society International, 2020) ;
    Rodrigo E. Peimbert-garcía
    ;
    Timothy Matis
    ;
    Jonathan Cuevas-ortuño
    Healthcare organizations have increasingly turned to Lean and Six Sigma (LSS) as management systems to achieve quality and efficiency in patient care. This study aims to classify this body of literature and to discover factors that enable and prevent successful LSS implementations. Peer-reviewed literature in journals that were published through 2018 in English language were sought through a search of multiple databases. The inclusion criterion was broad in that all areas of healthcare and interpretations of LSS were considered. The literature search yielded 368 publications. One third of the studies present a U.S. affiliation and only 19% has been conducted in developing countries. The case study is the most popular study type but only represents around 52% of the body of literature. Lean and the ED are preferred approach and setting, respectively. Factors that enable and prevent successful implementation were grouped by Managerial, Preparation, People, and Project relationships. There is a need for future literature to provide a longitudinal balanced view on the benefits and challenges of implementations, and for studies to follow experimental designs for statistical validity. This is the most inclusive review about LSS in healthcare as it includes different study types, healthcare settings and LSS tools together.
      1  37
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    The multi-depot k-traveling repairman problem
    (2022)
    Maria Elena Bruni
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    Sara Khodaparasti
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    Iris Martínez-Salazar
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    <jats:title>Abstract</jats:title><jats:p>In this paper, we study the multi-depot <jats:italic>k</jats:italic>-traveling repairman problem. This problem extends the traditional traveling repairman problem to the multi-depot case. Its objective, similar to the single depot variant, is the minimization of the sum of the arrival times to customers. We propose two distinct formulations to model the problem, obtained on layered graphs. In order to find feasible solutions for the largest instances, we propose a hybrid genetic algorithm where initial solutions are built using a splitting heuristic and a local search is embedded into the genetic algorithm. The efficiency of the mathematical formulations and of the solution approach are investigated through computational experiments. The proposed models are scalable enough to solve instances up to 240 customers.</jats:p>
    Scopus© Citations 4  1  10
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    A multi‐objective sustainable closed‐loop supply chain network problem with hybrid facilities
    <jats:title>Abstract</jats:title><jats:p>A sustainable closed‐loop supply chain network requires conjunctive implementation of reverse logistics in the supply chain, with decisions that consider economic, environmental, and social factors. In real life, the problem needs to be addressed by prioritizing targets or interacting between them to give a range of solutions to the decision maker. In this context, this work proposes a novel multi‐objective sustainable closed‐loop supply chain network problem based on the revised network design model with hybrid recovery centers minimizing (1) the total economic cost, (2) the CO<jats:sub>2</jats:sub> emission of vehicles used, and (3) the total obnoxious distance. The latter objective is a novel implementation of the social dimension of a sustainable model. A sensitivity analysis of the multi‐objective model is developed through ANOVA. A dataset of instances was generated to test the model and the solution methods, which are configured with AUGMECON2, a linear programming relaxation implemented to improve the CPU time, and AUGMECON2‐EXTENDED to obtain more solutions to avoid exploring all space of the solution. The results show that an AUGMECON2‐EXTENDED implementation outperforms all the selected performance metrics. These performance metrics include NPS, CPU time, RPOS, QM, and HV. The results show an improvement on average of at least , , , , and , respectively, in those metrics, in comparison to other implementations.</jats:p>
    Scopus© Citations 11  29