Examinando por Autor "Montero, Elizabeth"
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Ítem A Co-Evolutionary Scheme for Multi-Objective Evolutionary Algorithms Based on ϵ-Dominance(Institute of Electrical and Electronics Engineers Inc., 2019) Menchaca-Mendez, Adriana; Montero, Elizabeth; Antonio, Luis Miguel; Zapotecas-Martinez, Saul; Coello Coello, Carlos A. Coello; Riff, Maria-CristinaConvergence and diversity of solutions play an essential role in the design of multi-objective evolutionary algorithms (MOEAs). Among the available diversity mechanisms, the ϵ-dominance has shown a proper balance between convergence and diversity. When using ϵ-dominance, diversity is ensured by partitioning the objective space into boxes of size ϵ and, typically, a single solution is allowed at each of these boxes. However, there is no easy way to determine the precise value of ϵ. In this paper, we investigate how this goal can be achieved by using a co-evolutionary scheme that looks for the proper values of ϵ along the search without any need of a previous user's knowledge. We include the proposed co-evolutionary scheme into an MOEA based on ϵ-dominance giving rise to a new MOEA. We evaluate the proposed MOEA solving standard benchmark test problems. According to our results, it is a promising alternative for solving multi-objective optimization problems because three main reasons: 1) it is competitive concerning state-of-the-art MOEAs, 2) it does not need extra information about the problem, and 3) it is computationally efficient. © 2013 IEEE.Ítem A Constraint Programming Formulation of the Multi-Mode Resource-Constrained Project Scheduling Problem for the Flexible Job Shop Scheduling Problem(Institute of Electrical and Electronics Engineers Inc., 2023) Yuraszeck, Francisco; Montero, Elizabeth; Canut-De-Bon, Dario; Cuneo, Nicolas; Rojel, MaximilianoIn this work, a constraint programming (CP) formulation of the multi-mode resource-constrained project scheduling problem (MMRCPSP) is proposed for solving the flexible job shop scheduling problem (FJSSP) under the makespan minimization criterion. The resulting CP model allows us to tackle the classical instances of the FJSSP (such as where the operations of a given job follow a linear order). It can also handle FJSSP instances where the precedence relationships between operations are defined by an arbitrary directed acyclic graph (sequencing flexibility). The performance of our approach was tested using 271 classical FJSSP instances and 50 FJSSP instances with sequencing flexibility. We establish the validity of our approach by achieving an average relative percentage deviation of 3.04% and 0.18% when compared to the best-known lower and upper bounds, respectively. Additionally, we were able to contribute to the literature with ten new lower bounds and two new upper bounds. Our CP approach is relatively simple yet competitive and can be quickly applied and adapted by new practitioners in the area. © 2013 IEEE.Ítem A Heuristic Approach for Determining Efficient Vaccination Plans under a SARS-CoV-2 Epidemic Model(MDPI, 2023-02) Hazard-Valdés, Claudia; Montero, ElizabethIn this work, we propose a local search-based strategy to determine high-quality allocation of vaccines under restricted budgets and time periods. For this, disease spread is modeled as a SEAIR pandemic model. Subgroups are used to understand and evaluate movement restrictions and their effect on interactions between geographical divisions. A tabu search heuristic method is used to determine the number of vaccines and the groups to allocate them in each time period, minimizing the maximum number of infected people at the same time and the total infected population. Available data for COVID-19 daily cases was used to adjust the parameters of the SEAIR models in four study cases: Austria, Belgium, Denmark, and Chile. From these, we can analyze how different vaccination schemes are more beneficial for the population as a whole based on different reproduction numbers, interaction levels, and the availability of resources in each study case. Moreover, from these experiments, a strong relationship between the defined objectives is noticed.Ítem A Track-Based Conference Scheduling Problem(MDPI, 2022-11) Riquelme, Fabian; Montero, Elizabeth; Pérez Cáceres, Leslie; Rojas Morales, NicolásThe scheduling of conferences is a challenging task that aims at creating successful conference programs that fulfill an often wide variety of requirements. In this work, we focus on the problem of generating conference programs that organize talks into tracks: subevents within the conference that are group-related talks. The main contributions of this work can be organized into three scopes: literature review, problem formulation and benchmarking, and heuristic approach. We provide a literature review of conference scheduling approaches that organizes these approaches within a timetabling problem taxonomy. We also describe the main characteristics of the conference scheduling approaches in the literature and propose a classification scheme for such works. To study the scheduling of conferences that include tracks, we introduce the definition of the track-based conference scheduling problem, a new problem that incorporates tracks in the conference program. We provide a binary integer linear programming model formulation for this problem. Our formulation considers the availability of presenters, chairs, and organizers, the avoidance of parallel tracks, and best paper sessions, among other classical constraints of conference scheduling problems. Additionally, based on our formulation, we propose a simple instance-generation procedure that we apply to generate a set of artificial instances. We complete our work by proposing a heuristic method based on the simulated annealing metaheuristic for solving the track-based conference scheduling problem. We compare the results obtained by our heuristic approach and the Gurobi solver regarding execution time and solution quality. The results show that the proposed heuristic method is a practical approach for tackling the problem as it obtains solutions in a fraction of the time required by Gurobi, while Gurobi is also unable to obtain an optimal solution in the defined time for a subset of the instances. Finally, from a general perspective, this work provides a new conference scheduling problem formulation that can be extended in the future to include other features common in conference programs. Moreover, thanks to the instance generation procedure, this formulation can be used as a benchmark for designing and comparing new solving approaches. © 2022 by the authors.Ítem Application of meta-heuristic approaches in the spectral power clustering technique (SPCT) to improve the separation of partial discharge and electrical noise sources(Institute of Electrical and Electronics Engineers Inc., 2019) Ardila-Rey, Jorge Alfredo; Montero, Elizabeth; Poblete, Nicolás MedinaIn order to achieve an adequate diagnosis of the insulation system in any electrical asset it is necessary to carry out a proper separation process after measuring partial discharges (PD), since during the data acquisition it is very likely that simultaneous PD sources and electrical noise have been measured. Clearly, such separation will simplify the subsequent identification process, because the analysis will be done individually for each of the sources and not over the total of the signals. In this sense, the Spectral Power Clustering Technique (SPCT) has proven to be an effective technique when separating multiple sources acting simultaneously in a monitoring process. The effectiveness of this separation technique is fundamentally based on the proper selection of frequency bands or separation intervals, where the spectral power of the pulses is different for each source. In the case of selecting the wrong bands, the clusters will overlap, hiding the presence of the total number of sources. This research evaluates the performance of different meta-heuristic algorithms when applied to the SPCT for selecting separation intervals. The results obtained from the measurements made in different test objects will allow determining the most appropriate technique for separating PD sources and electrical noise acting simultaneously over an insulation system. © 2019 Oxford University Press. All rights reserved.Ítem Multi-Objective Location Problem for Bank Branches(Institute of Electrical and Electronics Engineers Inc., 2023) Montero, Elizabeth; Nicolis, Orietta; Reid, Samantha; Torres, MarceloAlthough current technologies allow simple online banking transactions, it is vital to guarantee access to bank branches both for customers and businesses. Banking branch interactions improve trust in bank institutions in everyday situations and emergencies. This research addresses the problem of the location of banking facilities. A set of objective functions related to socio-economic variables, geographical coverage and bankers preferences are considered. A multi-objective linear programming model is proposed to solve different versions of the problem considering a maximum radial distance coverage. The (mono/bi/multi) objective versions of the problem are analyzed by varying the values of the weights of objective functions in the proposed model that is then solved using AMPL Gurobi solver. The case study is carried out in Santiago de Chile with data from a local banking institution. In the results, the bank's initial situation is analyzed to contrast the solutions found later. This analysis is performed considering the mono-objective, bi-objective, and multi-objective nature of the studied problem. In all these cases, we analyzed changes in the structure of solutions as the coverage of the branches increases. The proposed model can quickly obtain feasible solutions according to the needs and available resources, allowing to replicate the analysis in different institutions under similar conditions considering strategically established priorities. © 2013 IEEE.