Nucamendi-Guillén, Samuel
Thumbnail Image
Preferred name
Nucamendi-Guillén, Samuel
Official Name
Nucamendi Guillén, Samuel Moisés
Alternative Name
snucamendi
Main Affiliation
ORCID
Scopus Author ID
57191972691
Researcher ID
M-8732-2018

Research Output
Now showing 1 - 10 of 29
No Thumbnail Available
Publication

A methodology for increasing revenue in fashion retail industry

2018 , Nucamendi-Guillén, Samuel , Moreno, Miguel A. , Mendoza, Abraham

Purpose Fashion retail companies typically exhibit short life-cycles, high volatility and low predictability. Therefore, their success is largely determined by the organisation’s flexibility and responsiveness. The purpose of this paper is to present a methodology to facilitate inventory control to minimise both shortages and excess inventory for a multi-product, multi-period finite time horizon inventory problem by using statistical and stochastic analysis. Design/methodology/approach The proposed methodology operates in two phases: the first phase consists on determining an aggregate plan (AP) that will be used for monitoring the behaviour of the items during the time horizon. This plan is obtained by statistically analysing historical data related to sales and inventory shortages and is used to determine a demand forecast during the time horizon that allows to handle with potential disruptions derived from real demand variations. Finally, supply replenishment policies are defined to facilitate the monitoring process during the second phase. For the second phase, the behaviour of real demand for every item is captured into a database and compared against its projected demand (from the AP). If needed, adjustments are made in the procurement of future deliveries to reduce the probability of having shortages and/or excess inventory. Findings A case study in a Mexican fashion retail company was conducted to assess the performance of the methodology. Results indicate that shortage in early periods can be reduced totally for certain products while, for others, the reduction is about 90.5 per cent. In addition, the incomes of the company were increased over 57 per cent. Research limitations/implications Even when the success of the methodology has been shown, cultural and behavioural factors were not considered. An extensive study is suggested to determine if these factors should be included to enhance the performance of the methodology. Practical implications A case study of a Mexican fashion retail company was conducted to assess the performance of the proposed methodology. The methodology is easy to implement and effectively and quickly responds to disruptions in the demand and it also significantly reduces the level of shortages while increasing sales and revenue for the company. Originality/value This paper proposes a methodology that is able to anticipate product’s behaviour from early weeks. Additionally, replenishment policies allow to quickly adjust future orders to guarantee the availability of items and minimise overstock.

View
No Thumbnail Available
Publication

An optimization framework for the distribution process of a manufacturing company balancing deliverymen workload and customer’s waiting times

2019 , José-Fernando Camacho-Vallejo , Nucamendi-Guillén, Samuel , Rosa G. González-Ramírez

View
No Thumbnail Available
Publication

The multi-depot k-traveling repairman problem

2022 , Maria Elena Bruni , Sara Khodaparasti , Iris Martínez-Salazar , Nucamendi-Guillén, Samuel

AbstractIn this paper, we study the multi-depot k-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.

View
No Thumbnail Available
Publication

Systematic Review of Literature on Lean and Six Sigma in Healthcare and Directions for Future Research

2020 , Nucamendi-Guillén, Samuel , 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.

View
No Thumbnail Available
Publication

A Bi-Level Vaccination Points Location Problem That Aims at Social Distancing and Equity for the Inhabitants

2023 , Edith Salinas , José-Fernando Camacho-Vallejo , Nucamendi-Guillén, Samuel

Designing efficient vaccination programs that consider the needs of the population is very relevant to prevent reoccurrence of the COVID-19 pandemic. The government needs to provide vaccination points to give out vaccine doses to the population. In this paper, the authors analyze the location of vaccination points whilst addressing the inhabitants’ preferences. Two objectives that prevent crowding of inhabitants are considered. The government aims for the minimum distance between located vaccination points is maximized, and for the number of inhabitants that attend the different vaccination points to be equitable. One of the key aspects of this problem is the assumption that inhabitants freely choose the located vaccination point to go. That decision affects the objectives of the government, since crowding at vaccination points may appear due to the inhabitants’ decisions. This problem is modeled as a bi-objective, bi-level program, in which the upper level is associated to the government and the lower level to the inhabitants. To approximate the Pareto front of this problem, a cross-entropy metaheuristic is proposed. The algorithm incorporates criteria to handle two objective functions in a simultaneous manner, and optimally solve the lower-level problem for each government decision. The proposed algorithm is tested over an adapted set of benchmark instances and pertinent analysis of the results is included. An important managerial insight is that locating far vaccination points does not lead us to a more equitable allocation of inhabitants.

View
No Thumbnail Available
Publication

An improved LINMAP for multicriteria decision: designing customized incentive portfolios in an organization

2022 , Jessica Rubiano-Moreno , Nucamendi-Guillén, Samuel , Alvaro Cordero-Franco , Alejandro Rodríguez-Magaña

AbstractThis study proposes three new versions of the well-known linear programming technique for multidimensional preference analysis (LINMAP). LINMAP addresses the multi-criteria decision problem by analyzing individual differences in preferences in relation to a set of prespecified incentives in multidimensional attribute space. The proposed models satisfy the decision-maker’s specific needs, such as determining a fixed number of incentives to be active or assigning a minimum/maximum weight for the active incentives. The performance of the developed models is assessed using information from a case study in which a decision-maker desires to determine an optimal portfolio of incentives based on the preferences of individuals surveyed. Experimental results confirm that the proposed models could obtain solutions according to the decision-maker’s needs, yielding a better selection of incentives to activate and their corresponding distribution of the weights than those of the original LINMAP model. Moreover, the consistency of the proposed models is evaluated by performing a sensitivity analysis over database variations of the case study and comparing the outcomes with the results provided in the original case study. Overall, this work is promising when creating a design portfolio, considering individuals’ different preferences.

View
No Thumbnail Available
Publication

Vehicle routing with cumulative objectives: A state of the art and analysis

2022 , Karina Corona-Gutiérrez , Nucamendi-Guillén, Samuel , Eduardo Lalla-Ruiz

View
No Thumbnail Available
Publication

The Capacitated Lot Sizing Problem with Batch Ordering: A MILP and Heuristic Approach

2019 , Macedo Barragán, Gustavo , Nucamendi-Guillén, Samuel , Olivares-Benitez, Elias , Rojas, Omar

View
No Thumbnail Available
Publication

A Formulation for the Stochastic Multi-Mode Resource-Constrained Project Scheduling Problem Solved with a Multi-Start Iterated Local Search Metaheuristic

2023 , Alfredo S. Ramos , Pablo A. Miranda-Gonzalez , Nucamendi-Guillén, Samuel , Olivares-Benitez, Elias

This research introduces a stochastic version of the multi-mode resource-constrained project scheduling problem (MRCPSP) and its mathematical model. In addition, an efficient multi-start iterated local search (MS-ILS) algorithm, capable of solving the deterministic MRCPSP, is adapted to deal with the proposed stochastic version of the problem. For its deterministic version, the MRCPSP is an NP-hard optimization problem that has been widely studied. The problem deals with a trade-off between the amount of resources that each project activity requires and its duration. In the case of the proposed stochastic formulation, the execution times of the activities are uncertain. Benchmark instances of projects with 10, 20, 30, and 50 activities from well-known public libraries were adapted to create test instances. The adapted algorithm proved to be capable and efficient for solving the proposed stochastic problem.

View
No Thumbnail Available
Publication

A multi‐objective sustainable closed‐loop supply chain network problem with hybrid facilities

2024 , Rodriguez-Escoto, Joel-Novi , Olivares-Benitez, Elias , Nucamendi-Guillén, Samuel , Julie Drzymalski

AbstractA 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 CO2 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.

View