Navegando por Palavras-chave "Scheduling"

Agora exibindo 1 - 3 de 3
  • Imagem de Miniatura
    Item
    Acesso aberto (Open Access)
    Abordagens para resolver o problema integrado de dimensionamento de lotes e scheduling em máquinas paralelas
    (Universidade Federal de São Paulo (UNIFESP), 2019-02-25) Carvalho, Desiree Maldonado [UNIFESP]; Rosset, Maria Cristina Vasconcelos Nascimento [UNIFESP]; Universidade Federal de São Paulo (UNIFESP)
    This study approaches the integrated lot sizing and scheduling problem (ILSSP), in which non-identical machines work in parallel with sequence-dependent non-triangular (NT) setup costs and times, setup carr y-over and capacity limitation. The aim of the studied ILSSP, called here ILSSP-NT on parallel machines, is to deter mine a production planning and tasks sequencing which meet the period demands without delay, in such a way that the total costs of production, machine setup and inventor y are minimized. The dearth of literature on the ILSSP-NT on parallel machines and the researchers interest to approach it motivated the study perfor med in this thesis. The aim of this thesis is the development of efficient solution methods to the ILSSP-NT on parallel machines, in particular, the proposal of matheuristics. To this end, it was performed an analysis of the main for mulations designed to the ILSSP-NT found in the literature, adapted to the problem with parallel machines. The pur pose was defining which for mulation could contribute to the best computational performance of solver CPLEX v. 12. 7. 1 limited by a period of time to solve instances from the literature, adapted to the problem with non-triangular setup costs and times. Besides this analysis, in a first moment, we performed a study on the capacitated lot sizing problem (CLSP) on parallel machines where we proposed a math-heuristic based in a Lagrangian heuristic and a method known as kernel search. Such method aimed the solution of the CLSP on parallel machines with SC and inspired the development of one of the methods proposed to the ILSSP-NT on parallel machines. The methods we propose to find solutions to the ILSSP-NT on parallel machines consist, virtually in the hybridization of relax-and-fix and fix-and-optimize methods with path-relinking and kernel search heuristics. Computational experiments attest the good performance of the proposed methods to find solutions to the CLSP, the ILSSP and the ILSSP-NT on parallel machines.
  • Nenhuma Miniatura disponível
    Item
    Somente Metadadados
    Hybrid method with CS and BRKGA applied to the minimization of tool switches problem
    (Pergamon-Elsevier Science Ltd, 2016) Chaves, A. A. [UNIFESP]; Lorena, L. A. N.; Senne, E. L. F.; Resende, M. G. C.
    The minimization of tool switches problem (MTSP) seeks a sequence to process a set of jobs so that the number of tool switches required is minimized. The MTSP is well known to be NP-hard. This paper presents a new hybrid heuristic based on the Biased Random Key Genetic Algorithm (BRKGA) and the Clustering Search (CS). The main idea of CS is to identify promising regions of the search space by generating solutions with a metaheuristic, such as BRKGA, and clustering them to be further explored with local search heuristics. The distinctive feature of the proposed method is to simplify this clustering process. Computational results for the MTSP considering instances available in the literature are presented to demonstrate the efficacy of the CS with BRKGA. (C) 2015 Elsevier Ltd. All rights reserved.
  • Imagem de Miniatura
    Item
    Acesso aberto (Open Access)
    Uma nova heurística para o problema de minimização de trocas de ferramentas
    (Universidade Federal de São Carlos, 2012-01-01) Chaves, Antonio Augusto [UNIFESP]; Senne, Edson Luiz França; Yanasse, Horacio Hideki [UNIFESP]; Universidade Federal de São Paulo (UNIFESP); Universidade Estadual Paulista (UNESP); Instituto Nacional de Pesquisas Espaciais
    The minimization of tool switches problem (MTSP) seeks a sequence to process a set of jobs so that the number of tool switches required is minimized. This study presents a new heuristic for the MTSP. This heuristic has two phases: a constructive phase, based on a graph where the vertices correspond to tools and there is an arc k = (i, j) linking vertices i and j if and only if the tools i and j are required to execute some job; and an improvement phase, based on an Iterated Local Search. Computational results show that the proposed heuristic has a good performance on the instances tested contributing to a significant reduction in the number of nodes generated by an enumerative algorithm.