Examinando por Autor "Canut-De-Bon, Dario"

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    Ítem
    A competitive constraint programming approach for the group shop scheduling problem
    (Elsevier B.V., 2023-03) Yuraszeck, Francisco; Mejia, Gonzalo; Canut-De-Bon, Dario
    In this paper, we propose a competitive Constraint Programming (CP) approach to solve the Group Shop Scheduling Problem (GSSP) under the makespan minimization criteria. Our contribution is two-fold: we provide a flexible mathematical formulation to solve the GSSP that can be used without change to solve other closed-related scheduling problems such as the Open Shop Scheduling Problem (OSSP), Job Shop Scheduling Problem (JSSP), and Mixed Shop Scheduling Problem (MSSP); and we improve several lower bounds and upper bounds from 130 classical GSSP instances from the literature. We evaluate our approach by comparing the performance with competitive methods mainly based on metaheuristics, where we were able to prove optimality in more than 85% of the instances in competitive running time, with a relative percentage deviation lower than 3% on average. In contrast to metaheuristics approaches, our CP method does not require calibrations of multiple parameters, several replicates for each instance, and complex computational coding to be competitive in both, solution quality and computational running times. © 2023 Elsevier B.V.. All rights reserved.
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    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, Maximiliano
    In 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.