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Author Osorio-Valenzuela, L.; Pereira, J.; Quezada, F.; Vasquez, O.C.
Title Minimizing the number of machines with limited workload capacity for scheduling jobs with interval constraints Type
Year 2019 Publication (up) 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 Pereira, J.; Ritt, M.; Vasquez, O.C.
Title A memetic algorithm for the cost-oriented robotic assembly line balancing problem Type
Year 2018 Publication (up) Computers & Operations Research Abbreviated Journal Comput. Oper. Res.
Volume 99 Issue Pages 249-261
Keywords Line balancing; Cost-oriented line balancing; Robotic assembly line; Hybrid algorithms
Abstract In order to minimize costs, manufacturing companies have been relying on assembly lines for the mass production of commodity goods. Among other issues, the successful operation of an assembly line requires balancing work among the stations of the line in order to maximize its efficiency, a problem known in the literature as the assembly line balancing problem, ALBP. In this work, we consider an ALBP in which task assignment and equipment decisions are jointly considered, a problem that has been denoted as the robotic ALBP. Moreover, we focus on the case in which equipment has different costs, leading to a cost-oriented formulation. In order to solve the problem, which we denote as the cost-oriented robotic assembly line balancing problem, cRALBP, a hybrid metaheuristic is proposed. The metaheuristic embeds results obtained for two special cases of the problem within a genetic algorithm in order to obtain a memetic algorithm, applicable to the general problem. An extensive computational experiment shows the advantages of the hybrid approach and how each of the components of the algorithm contributes to the overall ability of the method to obtain good solutions. (C) 2018 Elsevier Ltd. All rights reserved.
Address [Pereira, Jordi] Univ Adolfo Ibanez, Fac Engn & Sci, 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:000442059400019 Approved
Call Number UAI @ eduardo.moreno @ Serial 907
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Author Pereira, J.; Vasquez, O.C.
Title The single machine weighted mean squared deviation problem Type
Year 2017 Publication (up) 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
Permanent link to this record