Examinando por Materia "Makespan"

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    Ítem
    Combining LR and 2-opt for scheduling a single machine subject to job ready times and sequence dependent setup times
    (Institute of Industrial Engineers, 2014-01-01) Rojas-Santiago, M.; Muthuswamy, S.; Vélez-Gallego, M.C.; Montoya-Torres, J.R.; Universidad EAFIT. Departamento de Ingeniería de Producción; Gestión de Producción y Logística
    In this research, the job ready times and sequence-dependent setup times of a single machine scheduling problem are considered with the objective of makespan minimization. As the problem is NP-hard, a Lagrangean Relaxation (LR) approach is proposed to find an initial solution and a heuristic based on 2-opt was implemented to improve it. Extensive computational experiments showed that the proposed combination of LR and 2-opt is effective. Wide range of test problems from 25 to 75 jobs was studied. The performance of the proposed approach was compared with the results from a commercial solver.
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    Ítem
    GRASP Algorithm to Minimize Makespan in a No-Wait Flow Shop with Batch Processing Machines
    (Inst of Industrial Engineers; Cdr edition, 2012-05-19) Muthuswamy; Shanthi; Mario C. Vélez-Gallego; Maya; Jairo; Rojas; Miguel; Universidad EAFIT. Departamento de Ingeniería de Producción; Gestión de Producción y Logística
    Given a set of jobs and two Batch Processing Machines (BPMs) in a flow shop environment
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    Ítem
    Minimizing makespan in a two-machine no-wait flow shop with batch processing machines
    (Springer-Verlag, 2012-11-01) Muthuswamy, Shanthi; Vélez Gallego, Mario César; Rojas Santiago, Miguel; Maya Toro, Jairo; Muthuswamy, Shanthi; Vélez Gallego, Mario César; Rojas Santiago, Miguel; Maya Toro, Jairo; Universidad EAFIT. Grupo de Investigación Gestión de Producción y Logística; Universidad EAFIT. Departamento de Ingeniería de Producción; smuthuswamy@niu.edu; marvelez@eafit.edu.co; jmaya@eafit.edu.co; miguelrojas@uninorte.edu.co; Gestión de Producción y Logística
    Given a set of jobs and two batch processing machines (BPMs) arranged in a flow shop environment,the objective is to batch the jobs and sequence the batches such that the makespan is minimized. The job sizes, ready times, and processing times on the two BPMs are knowN -- The batch processing machines can process a batch of jobs as long as the total size of all the jobs assigned to a batch does not exceed its capacity -- Once the jobs are batched, the processing time of the batch on the first machine is equal to the longest processing job in the batch; processing time of the batch on the second machine is equal to the sum of processing times of all the jobs in the batch -- The batches cannot wait between two machines (i.e., no-wait) -- The problem under study is NP-hard -- We propose a mathematical formulation and present a particle swarm optimization (PSO) algorithm -- The solution quality and run time of PSO is compared with a commercial solver used to solve the mathematical formulation Experimental study clearly highlights the advantages, in terms of solution quality and run time, of using PSO to solve large-scale problems