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Author Alvarez-Miranda, E.; Pereira, J.; Vargas, C.; Vila, M.
Title (down) Variable-depth local search heuristic for assembly line balancing problems Type
Year 2022 Publication International Journal Of Production Research Abbreviated Journal Int. J. Prod. Res.
Volume 61 Issue 9 Pages 3103-3121
Keywords Assembly lines; Manufacturing; simple assembly line balancing; local search; variable-depth local search
Abstract Assembly lines are production flow systems wherein activities are organised around a line consisting of various workstations through which the product flows. At each station, the product is assembled through a subset of operations. The assembly line balancing problem (ALBP) consists of allocating operations between stations to maximise the system efficiency. In this study, a variable-depth local search algorithm is proposed for solving simple assembly line balancing problems (SALBPs), which are the most widely studied versions of the ALBP. Although the state-of-the-art techniques for solving the SALBP consist of exact enumeration-based methods or heuristics, this paper proposes a local search-based heuristic using variable-length sequences that allow the solution space to be efficiently explored. The proposed algorithm improves the best solution known for multiple instances reported in the literature, indicating that its efficiency is comparable to those of the state-of-the-art method for solving the SALBP. Moreover, the characteristics of the instances for which the proposed procedure provides a better solution than previously reported construction procedures are investigated.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0020-7543 ISBN Medium
Area Expedition Conference
Notes WOS:000800928700001 Approved
Call Number UAI @ alexi.delcanto @ Serial 1578
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Author Pereira, J.; Vasquez, O.C.
Title (down) The single machine weighted mean squared deviation problem Type
Year 2017 Publication European Journal Of Operational Research Abbreviated Journal Eur. J. Oper. Res.
Volume 261 Issue 2 Pages 515-529
Keywords Scheduling; Single machine; JIT; Branch-and-cut; Dominance properties
Abstract This paper studies a single machine problem related to the just-In-Time (JIT) production objective in which the goal is to minimize the sum of weighted mean squared deviation of the completion times with respect to a common due date. In order to solve the problem, several structural and dominance properties of the optimal solution are investigated. These properties are then integrated within a branch and-cut approach to solve a time-indexed formulation of the problem. The results of a computational experiment with the proposed algorithm show that the method is able to optimally solve instances with up to 300 jobs within reduced running times, improving other integer programming approaches. (C) 2017 Elsevier B.V. All rights reserved.
Address [Pereira, Jordi] Univ Adolfo Ibanez, Dept Engn & Sci, Av Padre Hurtado 750,Off C216, Vina Del Mar, Chile, Email: jorge.pereira@uai.cl;
Corporate Author Thesis
Publisher Elsevier Science Bv Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0377-2217 ISBN Medium
Area Expedition Conference
Notes WOS:000401206300009 Approved
Call Number UAI @ eduardo.moreno @ Serial 730
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Author Pereira, J.
Title (down) The robust (minmax regret) single machine scheduling with interval processing times and total weighted completion time objective Type
Year 2016 Publication Computers & Operations Research Abbreviated Journal Comput. Oper. Res.
Volume 66 Issue Pages 141-152
Keywords Scheduling; Single machine; Uncertainty; Robust optimization; Branch-and-bound
Abstract Single machine scheduling is a classical optimization problem that depicts multiple real life systems in which a single resource (the machine) represents the whole system or the bottleneck operation of the system. In this paper we consider the problem under a weighted completion time performance metric in which the processing time of the tasks to perform (the jobs) are uncertain, but can only take values from closed intervals. The objective is then to find a solution that minimizes the maximum absolute regret for any possible realization of the processing times. We present an exact branch-and-bound method to solve the problem, and conduct a computational experiment to ascertain the possibilities and limitations of the proposed method. The results show that the algorithm is able to optimally solve instances of moderate size (25-40 jobs depending on the characteristics of the instance). (c) 2015 Elsevier Ltd. All rights reserved.
Address [Pereira, Jordi] Univ Adolfo Ibanez, Fac Sci & Engn, Vina Del Mar, Chile, Email: jorge.pereira@uai.cl
Corporate Author Thesis
Publisher Pergamon-Elsevier Science Ltd Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0305-0548 ISBN Medium
Area Expedition Conference
Notes WOS:000366779900013 Approved
Call Number UAI @ eduardo.moreno @ Serial 558
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Author Pereira, J.
Title (down) The robust (minmax regret) assembly line worker assignment and balancing problem Type
Year 2018 Publication Computers & Operations Research Abbreviated Journal Comput. Oper. Res.
Volume 93 Issue Pages 27-40
Keywords Production; Line balancing; Robust optimization; Minmax regret
Abstract Line balancing aims to assign the assembly tasks to the stations that compose the assembly line. A recent body of literature has been devoted to heterogeneity in the assembly process introduced by different workers. In such an environment, task times depend on the worker performing the operation and the problem aims at assigning tasks and workers to stations in order to maximize the throughput of the line. In this work, we consider an interval data version of the assembly line worker assignment and balancing problem (ALWABP) in which it is assumed that lower and upper bounds for the task times are known, and the objective is to find an assignment of tasks and workers to the workstations such that the absolute maximum regret among all of the possible scenarios is minimized. The relationship with other interval data minmax regret (IDMR) problems is investigated, the inapplicability of previous approximation methods is studied, regret evaluation is considered, and exact and heuristic solution methods are proposed and analyzed. The results of the proposed methods are compared in a computational experiment, showing the applicability of the method and the theoretical results to solve the problem under study. Additionally, these results are not only applicable to the problem in hand, but also to a more general class of problems. (C) 2018 Elsevier Ltd. All rights reserved.
Address [Pereira, Jordi] Univ Adolfo Ibanez, Dept Sci & Engn, Av Padre Hurtado 750,Off C216, Vina Del Mar, Chile, Email: jorge.pereira@uai.cl
Corporate Author Thesis
Publisher Pergamon-Elsevier Science Ltd Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0305-0548 ISBN Medium
Area Expedition Conference
Notes WOS:000427339800003 Approved
Call Number UAI @ eduardo.moreno @ Serial 838
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Author Campos-Valdes, C.; Alvarez-Miranda, E.; Quiroga, MM; Pereira, J.; Duran, FL.
Title (down) The Impact of Candidates' Profile and Campaign Decisions in Electoral Results: A Data Analytics Approach Type
Year 2021 Publication Mathematics Abbreviated Journal Mathematics
Volume 9 Issue 8 Pages 902
Keywords Chilean parliamentary election; candidate profiles; campaign efforts; territorial deployment
Abstract In recent years, a wide range of techniques has been developed to predict electoral results and to measure the influence of different factors in these results. In this paper, we analyze the influence of the political profile of candidates (characterized by personal and political features) and their campaign effort (characterized by electoral expenditure and by territorial deployment strategies retrieved from social networks activity) on the electoral results. This analysis is carried out by using three of the most frequent data analyitcs algorithms in the literature. For our analysis, we consider the 2017 Parliamentary elections in Chile, which are the first elections after a major reform of the electoral system, that encompassed a transition from a binomial to a proportional system, a modification of the districts' structure, an increase in the number of seats, and the requirement of gender parity in the lists of the different coalitions. The obtained results reveal that, regardless of the political coalition, the electoral experience of candidates, in particular in the same seat they are running for (even when the corresponding district is modified), is by large the most influential factor to explain the electoral results. However, the attained results show that the influence of other features, such as campaign expenditures, depends on the political coalition. Additionally, by means of a simulation procedure, we show how different levels of territorial deployment efforts might impact on the results of candidates. This procedure could be used by parties and coalitions when planning their campaign strategies.
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Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2227-7390 ISBN Medium
Area Expedition Conference
Notes WOS:000644524000001 Approved
Call Number UAI @ alexi.delcanto @ Serial 1377
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Author Melo, I.C.; Queiroz, G.A.; Junior, P.N.A.; de Sousa, T.B.; Yushimito, W.F.; Pereira, J.
Title (down) Sustainable digital transformation in small and medium enterprises (SMEs): A review on performance Type
Year 2023 Publication Heliyon Abbreviated Journal Heliyon
Volume 9 Issue 3 Pages e13908
Keywords Digitalization; Small and medium-sized enterprises (SMEs); Industry 40Triple bottom line (TBL) of sustainability; Sustainable development goals (SDG)
Abstract Small and medium enterprises (SMEs) are responsible for 90% of all business and 50% of employment globally, mostly female jobs. Therefore, measuring SMEs' performance under the digital transformation (DT) through methods that encompass sustainability represents an essential tool for reducing poverty and gender inequality (United Nations Sustainable Development Goals). We aimed to describe and analyze the state-of-art performance evaluations of digital transformation in SMEs, mainly focusing on performance measurement. Also, we aimed to determine whether the tools encompass the three pillars of sustainability (environmental, social, and economic). Through a systematic literature review (SLR), a search on Web of Science (WoS) and Scopus resulted in the acceptance of 74 peer-reviewed papers published until December 2021. Additionally, a bibliometrics investigation was executed. Although there was no time restriction, the oldest paper was published in 2016, indicating that DT is a new research topic with increasing interest. Italy, China, and Finland are the countries that have the most published on the theme. Based on the results, a conceptual framework is proposed. Also, two future research directions are presented and discussed, one for theoretical and another for practical research. Among the theoretical development, it is essential to work on a widely accepted SME definition. Among the practical research, nine directions are identified-e.g., applying big data, sectorial and regional prioritization, cross-temporal investigations etc. Researchers can follow the presented avenues and roads to guide their researchers toward the most relevant topics with the most urgent necessity of investigation.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2405-8440 ISBN Medium
Area Expedition Conference
Notes WOS:000968115200001 Approved
Call Number UAI @ alexi.delcanto @ Serial 1782
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Author Pereira, J.
Title (down) Procedures for the bin packing problem with precedence constraints Type
Year 2016 Publication European Journal Of Operational Research Abbreviated Journal Eur. J. Oper. Res.
Volume 250 Issue 3 Pages 794-806
Keywords Bin packing; Precedence constraints; Lower bounds; Dynamic programming; Branch-and-bound
Abstract The bin packing problem with precedence constraints (BPP-P) is a recently proposed variation of the classical bin packing problem (BPP), which corresponds to a basic model featuring many underlying characteristics of several scheduling and assembly line balancing problems. The formulation builds upon the BPP by incorporating precedence constraints among items, which force successor items to be packed into later bins than their predecessors. In this paper we propose a dynamic programming based heuristic, and a modified exact enumeration procedure to solve the problem. These methods make use of several new lower bounds and dominance rules tailored for the problem in hand. The results of a computational experiment show the effectiveness of the proposed methods, which are able to close all of the previous open instances from the benchmark instance set within very reduced running times. (C) 2015 Elsevier B.V. and Association of European Operational Research Societies (EURO) within the International Federation of Operational Research Societies (IFORS). All rights reserved.
Address [Pereira, Jordi] Univ Adolfo Ibanez, Fac Sci & Engn, Ave Padre Hurtado 750,Off C216, Vina Del Mar, Chile, Email: jorge.pereira@uai.cl
Corporate Author Thesis
Publisher Elsevier Science Bv Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0377-2217 ISBN Medium
Area Expedition Conference
Notes WOS:000369192500011 Approved
Call Number UAI @ eduardo.moreno @ Serial 581
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Author Alvarez-Miranda, E.; Pereira, J.
Title (down) On the complexity of assembly line balancing problems Type
Year 2019 Publication Computers & Operations Research Abbreviated Journal Comput. Oper. Res.
Volume 108 Issue Pages 182-186
Keywords Line balancing; Complexity; Bin packing
Abstract Assembly line balancing is a family of combinatorial optimization problems that has been widely studied in the literature due to its simplicity and industrial applicability. Most line balancing problems are NP-hard as they subsume the bin packing problem as a special case. Nevertheless, it is common in the line balancing literature to cite [A. Gutjahr and G. Nemhauser, An algorithm for the line balancing problem, Management Science 11 (1964) 308-315] in order to assess the computational complexity of the problem. Such an assessment is not correct since the work of Gutjahr and Nemhauser predates the concept of NP-hardness. This work points at over 50 publications since 1995 with the aforesaid error. (C) 2019 Elsevier Ltd. All rights reserved.
Address [Alvarez-Miranda, Eduardo] Univ Talca, Dept Ind Engn, Curico, Chile, Email: jorge.pereira@uai.cl
Corporate Author Thesis
Publisher Pergamon-Elsevier Science Ltd Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0305-0548 ISBN Medium
Area Expedition Conference
Notes WOS:000471733300014 Approved
Call Number UAI @ eduardo.moreno @ Serial 1015
Permanent link to this record
 

 
Author Mejia, G.; Pereira, J.
Title (down) Multiobjective scheduling algorithm for flexible manufacturing systems with Petri nets Type
Year 2020 Publication Journal Of Manufacturing Systems Abbreviated Journal J. Manuf. Syst.
Volume 54 Issue Pages 272-284
Keywords Machine scheduling; Multi-objective optimization; Petri nets
Abstract In this work, we focus on general multi-objective scheduling problems that can be modeled using a Petri net framework. Due to their generality, Petri nets are a useful abstraction that captures multiple characteristics of real-life processes. To provide a general solution procedure for the abstraction, we propose three alternative approaches using an indirect scheme to represent the solution: (1) a genetic algorithm that combines two objectives through a weighted fitness function, (2) a non dominated sorting genetic algorithm (NSGA-II) that explicitly addresses the multi-objective nature of the problem and (3) a multi-objective local search approach that simultaneously explores multiple candidate solutions. These algorithms are tested in an extensive computational experiment showing the applicability of this general framework to obtain quality solutions.
Address [Mejia, Gonzalo] Univ La Sabana, Fac Engn, Campus Puente del Comun, Chia, Colombia, Email: gonzalo.mejia@unisabana.edu.co;
Corporate Author Thesis
Publisher Elsevier Sci Ltd Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0278-6125 ISBN Medium
Area Expedition Conference
Notes WOS:000521511500021 Approved
Call Number UAI @ eduardo.moreno @ Serial 1154
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Author Lagos, F.; Pereira, J.
Title (down) Multi-arme d bandit-base d hyper-heuristics for combinatorial optimization problems Type
Year 2023 Publication European Journal Of Operational Research Abbreviated Journal Eur. J. Oper. Res.
Volume 312 Issue 1 Pages 70-91
Keywords Metaheuristics; Combinatorial optimization; Hyper-heuristics; Machine learning
Abstract There are significant research opportunities in the integration of Machine Learning (ML) methods and Combinatorial Optimization Problems (COPs). In this work, we focus on metaheuristics to solve COPs that have an important learning component. These algorithms must explore a solution space and learn from the information they obtain in order to find high-quality solutions. Among the metaheuristics, we study Hyper-Heuristics (HHs), algorithms that, given a number of low-level heuristics, iteratively select and apply heuristics to a solution. The HH we consider has a Markov model to produce sequences of low-level heuristics, which we combine with a Multi-Armed Bandit Problem (MAB)-based method to learn its parameters. This work proposes several improvements to the HH metaheuristic that yields a better learning for solving problem instances. Specifically, this is the first work in HHs to present Exponential Weights for Exploration and Exploitation (EXP3) as a learning method, an algorithm that is able to deal with adversarial settings. We also present a case study for the Vehicle Routing Problem with Time Windows (VRPTW), for which we include a list of low-level heuristics that have been proposed in the literature. We show that our algorithms can handle a large and diverse list of heuristics, illustrating that they can be easily configured to solve COPs of different nature. The computational results indicate that our algorithms are competitive methods for the VRPTW (2.16% gap on average with respect to the best known solutions), demonstrating the potential of these algorithms to solve COPs. Finally, we show how algorithms can even detect low-level heuristics that do not contribute to finding better solutions to the problem.& COPY
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0377-2217 ISBN Medium
Area Expedition Conference
Notes WOS:001060399900001 Approved
Call Number UAI @ alexi.delcanto @ Serial 1877
Permanent link to this record
 

 
Author Pereira, J.
Title (down) Modelling and solving a cost-oriented resource-constrained multi-model assembly line balancing problem Type
Year 2018 Publication International Journal Of Production Research Abbreviated Journal Int. J. Prod. Res.
Volume 56 Issue 11 Pages 3994-4016
Keywords assembly line balancing; combinatorial optimisation; lower bound; heuristics; estimation of distribution algorithm
Abstract A line balancing problem considers the assignment of operations to workstations in an assembly line. While assembly lines are usually associated to mass production of standardised goods, their advantages have led to their widespread use whenever a product-oriented production system is applicable and the benefits of the labour division and specialisation are significant, even when some of its characteristics may deviate from classical assembly lines. In this work, we study a line balancing problem found in the textile industry in which the line must be balanced for multiple types of goods taking into account resource requirements. In order to solve the problem, a hybrid method that combines classical methods for line balancing with an Estimation of Distribution Algorithm is proposed. Computational experiments show that the new procedure improves upon the state of the art when compared using a benchmark set derived from the literature, as well as when compared using data from the manufacturer that originated this research work.
Address [Pereira, Jordi] Univ Adolfo Ibanez, Fac Engn & Sci, Vina Del Mar, Chile, Email: jorge.pereira@uai.cl
Corporate Author Thesis
Publisher Taylor & Francis Ltd Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0020-7543 ISBN Medium
Area Expedition Conference
Notes WOS:000438403800013 Approved
Call Number UAI @ eduardo.moreno @ Serial 889
Permanent link to this record
 

 
Author Osorio-Valenzuela, L.; Pereira, J.; Quezada, F.; Vasquez, O.C.
Title (down) Minimizing the number of machines with limited workload capacity for scheduling jobs with interval constraints Type
Year 2019 Publication Applied Mathematical Modelling Abbreviated Journal Appl. Math. Model.
Volume 74 Issue Pages 512-527
Keywords Scheduling; Parallel machines; Interval and workload constraints; Branch-and-price
Abstract In this paper, we consider a parallel machine scheduling problem in which machines have a limited workload capacity and jobs have deadlines and release dates. The problem is motivated by the operation of energy storage management systems for microgrids under emergency conditions and generalizes some problems that have already been studied in the literature for their theoretical value. In this work, we propose heuristic and exact algorithms to solve the problem. The heuristics are adaptations of classical bin packing heuristics in which additional conditions on the feasibility of a solution are imposed, whereas the exact method is a branch-and-price approach. The results show that the branch-andprice approach is able to optimally solve random instances with up to 250 jobs within a time limit of one hour, while the heuristic procedures provide near optimal solution within reduced running times. Finally, we also provide additional complexity results for a special case of the problem. (C) 2019 Elsevier Inc. All rights reserved.
Address [Osorio-Valenzuela, Luis] Univ Santiago Chile, Elect Engn Dept, Santiago, Chile, Email: luis.osoriov@usach.cl;
Corporate Author Thesis
Publisher Elsevier Science Inc Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0307-904x ISBN Medium
Area Expedition Conference
Notes WOS:000474317800031 Approved
Call Number UAI @ eduardo.moreno @ Serial 1013
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Author Averbakh, I.; Pereira, J.
Title (down) Lateness Minimization in Pairwise Connectivity Restoration Problems Type
Year 2018 Publication Informs Journal On Computing Abbreviated Journal INFORMS J. Comput.
Volume 30 Issue 3 Pages 522-538
Keywords combinatorial optimization; networks: scheduling; programming: branch and bound; network restoration; network construction; integrated network design and scheduling
Abstract A network is given whose edges need to be constructed (or restored after a disaster). The lengths of edges represent the required construction/restoration times given available resources, and one unit of length of the network can be constructed per unit of time. All points of the network are accessible for construction at any time. For each pair of vertices, a due date is given. It is required to find a construction schedule that minimizes the maximum lateness of all pairs of vertices, where the lateness of a pair is the difference between the time when the pair becomes connected by an already constructed path and the pair's due date. We introduce the problem and analyze its structural properties, present a mixed-integer linear programming formulation, develop a number of lower bounds that are integrated in a branch-and-bound algorithm, and discuss results of computational experiments both for instances based on randomly generated networks and for instances based on 2010 Chilean earthquake data.
Address [Averbakh, Igor] Univ Toronto Scarborough, Dept Management, Toronto, ON M1C 1A4, Canada, Email: averbakh@utsc.uturonto.ca;
Corporate Author Thesis
Publisher Informs Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1091-9856 ISBN Medium
Area Expedition Conference
Notes WOS:000449096000008 Approved
Call Number UAI @ eduardo.moreno @ Serial 924
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Author Ritt, M.; Pereira, J.
Title (down) Heuristic and exact algorithms for minimum-weight non-spanning arborescences Type
Year 2020 Publication European Journal Of Operational Research Abbreviated Journal Eur. J. Oper. Res.
Volume 287 Issue 1 Pages 61-75
Keywords Minimum-weight non-spanning arborescence; Heuristic; Iterated Local Search; Branch-and-cut
Abstract We address the problem of finding an arborescence of minimum total edge weight rooted at a given vertex in a directed, edge-weighted graph. If the arborescence must span all vertices the problem is solvable in polynomial time, but the non-spanning version is NP-hard. We propose reduction rules which determine vertices that are required or can be excluded from optimal solutions, a modification of Edmonds algorithm to construct arborescences that span a given set of selected vertices, and embed this procedure into an iterated local search for good vertex selections. Moreover, we propose a cutset-based integer linear programming formulation, provide different linear relaxations to reduce the number of variables in the model and solve the reduced model using a branch-and-cut approach. We give extensive computational results showing that both the heuristic and the exact methods are effective and obtain better solutions on instances from the literature than existing approaches, often in much less time. (C) 2020 Elsevier B.V. All rights reserved.
Address [Ritt, Marcus] Univ Fed Rio Grande do Sul, Inst Informat, Av Bento Goncalves 9500, Porto Alegre, RS, Brazil, Email: marcus.ritt@inf.ufrgs.br;
Corporate Author Thesis
Publisher Elsevier Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0377-2217 ISBN Medium
Area Expedition Conference
Notes WOS:000541072800005 Approved
Call Number UAI @ eduardo.moreno @ Serial 1187
Permanent link to this record
 

 
Author Pereira, J.; Ritt, M.
Title (down) Exact and heuristic methods for a workload allocation problem with chain precedence constraints Type
Year 2023 Publication European Journal Of Operational Research Abbreviated Journal Eur. J. Oper. Res.
Volume 309 Issue 1 Pages 387-398
Keywords Manufacturing; Assembly line balancing; Worker allocation; Dynamic programming; Branch and bound
Abstract Industrial manufacturing is often organized in assembly lines where a product is assembled on a se-quence of stations, each of which executes some of the assembly tasks. A line is balanced if the maximum total execution time of any station is minimal. Commonly, the task execution order is constrained by precedences, and task execution times are independent of the station performing the task. Here, we con -sider a recent variation, called the “(Calzedonia) Workload Allocation Problem” (WAP), where the prece-dences form a chain, and the execution time of a task depends on the worker executing it. This problem was recently proposed by Battarra et al. (2020) and it is a special case of the Assembly Line Worker As-signment and Balancing Problem Miralles et al. (2007) where precedence relations are arbitrary. In this paper we consider the computational complexity of the problem and prove its NP-hardness. To solve the problem, we provide different lower bounds and exact and heuristic procedures. The performance of the proposed methods is tested on previously proposed instances and on new, larger instances with the same characteristics. The results show that the proposed methods can solve instances with up to about 40 0 0 tasks and 29 workers, doubling the size of the instances that previously could be solved to optimality.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0377-2217 ISBN Medium
Area Expedition Conference
Notes WOS:000970067900001 Approved
Call Number UAI @ alexi.delcanto @ Serial 1794
Permanent link to this record
 

 
Author Melo, I.C.; Alves, P.N.; Queiroz, G.A.; Yushimito, W.; Pereira, J.
Title (down) Do We Consider Sustainability When We Measure Small and Medium Enterprises' (SMEs') Performance Passing through Digital Transformation? Type
Year 2023 Publication Sustainability Abbreviated Journal Sustainability
Volume 15 Issue 6 Pages 4917
Keywords digitalization; small- and medium-sized enterprises (SMEs); Industry 4; 0; topic modeling; latent dirichlet allocation (LDA); triple bottom line of sustainability
Abstract Small-medium enterprises (SMEs) represent 90% of business globally. Digital Transformation (DT) affects SMEs differently from larger companies because although SMEs have more flexibility and agility for adapting to new circumstances, they also have more limited resources and specialization capabilities. Thus, it is fundamental to measure SMEs' performance considering different perspectives. Here, we describe and analyze the state-of-the-art of DT in SMEs, focusing on performance measurement. We center on whether the tools used by SMEs encompass the triple bottom line of sustainability (i.e., environmental, social, and economic aspects). To do so, in December 2021, we performed a comprehensive systematic literature review (SLR) on the Web of Science and Scopus. In addition, we also explored a novel approach for SLR: topic modeling with a machine learning technique (Latent Dirichlet Allocation). The differences and interchangeability of both methods are discussed. The findings show that sustainability is treated as a separate topic in the literature. The social and environmental aspects are the most neglected. This paper contributes to sustainable development goals (SDGs) 1, 5, 8, 9, 10, and 12. A conceptual framework and future research directions are proposed. Thus, this paper is also valuable for policymakers and SMEs switching their production paradigm toward sustainability and DT.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2071-1050 ISBN Medium
Area Expedition Conference
Notes WOS:000958416000001 Approved
Call Number UAI @ alexi.delcanto @ Serial 1770
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Author Alvarez-Miranda, E.; Pereira, J.
Title (down) Designing and constructing networks under uncertainty in the construction stage: Definition and exact algorithmic approach Type
Year 2017 Publication Computers & Operations Research Abbreviated Journal Comput. Oper. Res.
Volume 81 Issue Pages 178-191
Keywords Network design; Network construction; Two-stage robust optimization; Exact algorithms
Abstract The present work proposes a novel Network Optimization problem whose core is to combine both network design and network construction scheduling under uncertainty into a single two-stage robust optimization model. The first-stage decisions correspond to those of a classical network design problem, while the second-stage decisions correspond to those of a network construction scheduling problem (NCS) under uncertainty. The resulting problem, which we will refer to as the Two-Stage Robust Network Design and Construction Problem (2SRNDC), aims at providing a modeling framework in which the design decision not only depends on the design costs (e.g., distances) but also on the corresponding construction plan (e.g., time to provide service to costumers). We provide motivations, mixed integer programming formulations, and an exact algorithm for the 2SRNDC. Experimental results on a large set of instances show the effectiveness of the model in providing robust solutions, and the capability of the proposed algorithm to provide good solutions in reasonable running times. (C) 2017 Elsevier Ltd. All rights reserved.
Address [Alvarez-Miranda, Eduardo] Univ Talca, Dept Ind Engn, Curico, Chile, Email: ealvarez@utalca.cl
Corporate Author Thesis
Publisher Pergamon-Elsevier Science Ltd Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0305-0548 ISBN Medium
Area Expedition Conference
Notes WOS:000394079400015 Approved
Call Number UAI @ eduardo.moreno @ Serial 706
Permanent link to this record
 

 
Author Alvarez-Miranda, E.; Chace, S.; Pereira, J.
Title (down) Assembly line balancing with parallel workstations Type
Year 2021 Publication International Journal Of Production Research Abbreviated Journal Int. J. Prod. Res.
Volume 59 Issue 21 Pages 6486-6506
Keywords Line balancing; parallel stations; dynamic programming; hybrid metaheuristic; matheuristic
Abstract The simple assembly line balancing problem (SALBP) considers work division among different workstations of a serially arranged assembly process to maximise its efficiency under workload (cumulative) and technological (precedence) constraints. In this work, we consider a variant of the SALBP which allows parallel workstations. To study the effect of parallel stations, we propose a new problem (the parallel station assembly line balancing problem or PSALBP) in which the objective is to minimise the number of parallel stations required to obtain the maximum theoretical efficiency of the assembly process. We study the complexity of the problem and identify a polynomially solvable case. This result is then used as a building block for the development of a heuristic solution procedure. Finally, we carry out a computational experiment to identify the characteristics of assembly lines that may benefit from station paralleling and to evaluate the performance of the proposed heuristic.
Address [alvarez-Miranda, Eduardo] Univ Talca, Fac Engn, Dept Ind Engn, Curico, Chile, Email: jorge.pereira@uai.cl
Corporate Author Thesis
Publisher Taylor & Francis Ltd Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0020-7543 ISBN Medium
Area Expedition Conference
Notes WOS:000569837900001 Approved
Call Number UAI @ alexi.delcanto @ Serial 1243
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Author Alvarez-Miranda, E.; Pereira, J.; Vila, M.
Title (down) Analysis of the simple assembly line balancing problem complexity Type
Year 2023 Publication Computers & Operations Research Abbreviated Journal Comput. Oper. Res.
Volume 159 Issue Pages 106323
Keywords Manufacturing; Assembly line balancing; Packing; Precedence constraints; Instance sets
Abstract The simple assembly line balancing problem (SALBP) involves the determination of the assignment of elementary assembly operations to the workstations of the assembly line for the manufacture of a final product, with the objective of maximising assembly efficiency. In addition to its practicality, the SALBP can be considered as an extension of the bin packing problem (BPP) to account for the precedence relations between items. These constraints introduce an ordering component to the problem, which increases the complexity of SALBP resolution. However, previous studies indicated that precedence constraints do not play an important role in the capacity of state-of-the-art procedures to solve benchmark instances to optimality. In this study, we analysed the influences of different features of an SALBP instance on the performance of state-of-the-art solution methods for the abovementioned problem. First, we provide an alternative proof of complexity for the SALBP that uses precedence constraints to demonstrate its non-deterministic polynomial time (NP)-complete status, followed by a new set of benchmark instances directed towards an empirical analysis of the different features of SALBP instances. The experimental results revealed that the packing features of the SALBP are a major source of the perceived difficulty for any instance; however, precedence constraints play a role in the performance of these solution procedures. Specifically, the number of precedence constraints plays an important role in the results obtained from state-of-the-art methods. In addition to the analysis, certain issues that were identified in the publicly available implementations of the state-of-the-art method for resolving this problem were addressed in this study.
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Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0305-0548 ISBN Medium
Area Expedition Conference
Notes WOS:001033536100001 Approved
Call Number UAI @ alexi.delcanto @ Serial 1849
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Author Opazo, D.; Moreno, S.; Alvarez-Miranda, E.; Pereira, J.
Title (down) Analysis of First-Year University Student Dropout through Machine Learning Models: A Comparison between Universities Type
Year 2021 Publication Mathematics Abbreviated Journal Mathematics
Volume 20 Issue 9 Pages 2599
Keywords machine learning; first-year student dropout; universities
Abstract Student dropout, defined as the abandonment of a high education program before obtaining the degree without reincorporation, is a problem that affects every higher education institution in the world. This study uses machine learning models over two Chilean universities to predict first-year engineering student dropout over enrolled students, and to analyze the variables that affect the probability of dropout. The results show that instead of combining the datasets into a single dataset, it is better to apply a model per university. Moreover, among the eight machine learning models tested over the datasets, gradient-boosting decision trees reports the best model. Further analyses of the interpretative models show that a higher score in almost any entrance university test decreases the probability of dropout, the most important variable being the mathematical test. One exception is the language test, where a higher score increases the probability of dropout.
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Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2227-7390 ISBN Medium
Area Expedition Conference
Notes Approved
Call Number UAI @ alexi.delcanto @ Serial 1463
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