Gestión de Producción y Logística

URI permanente para esta comunidad

https://hdl.handle.net/10784/4313

Realiza proyectos de investigación en conjunto con el sector industrial y/o gobierno, con el propósito de dar solución a problemas que se presenten en las áreas de producción y logística de las empresas, buscando así mejorar la productividad y competitividad de las mismas.

Líneas de investigación: Gestión de Producción y Logística Industrial.
Código Minciencias: COL0025371.
Categoría 2019: A.
Escuela: Ingeniería.
Departamento académico: Ingeniería de Producción.
Coordinador: Carlos Alberto Castro Zuluaga.
Correo electrónico: ccastro@eafit.edu.co

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Mostrando 1 - 3 de 3

Heuristic to allocate intermediate buffer storage capacities in a production line subject to machine breakdowns
(Production and Operations Management Society (POMS), 2013-05-03) Vélez Gallego, Mario César; Jaramillo Jiménez, Jhull Breynner; Universidad EAFIT. Departamento de Ingeniería de Producción; marvelez@eafit.edu.co; Gestión de Producción y Logística
In this research proposal we consider a production line subject to random failures at each workstation and operating under a make-to-stock policy -- Every time a workstation fails, a corrective maintenance activity is triggered to repair the workstation -- In order to palliate the effect of the random failures in the performance of the system, intermediate buffers are placed in-between workstations -- An inventory holding cost is associated to eachbuffer -- The research objective in this work is to allocate capacity to each intermediate buffer in the line so that the average cost per time unit is minimized while the average service level is kept above a minimum pre-specified value -- In this paper we assume that unsatisfied demand is lost and the service level is defined as the long term proportion of satisfied demand -- A greedy simulation–based heuristic is presented to find a feasible solution to the problem
Makespan minimization in a job shop with a BPM using simulated annealing
(Springer London, 2013-03-08) Rojas Santiago, Miguel; Vélez Gallego, Mario César; Damodaran, Purushothaman; Muthuswamy, Shanthi; Rojas Santiago, Miguel; Vélez Gallego, Mario César; Damodaran, Purushothaman; Muthuswamy, Shanthi; Universidad EAFIT. Departamento de Ingeniería de Producción; marvelez@eafit.edu.co; Gestión de Producción y Logística
A scheduling problem commonly observed in the metal working industry has been studied in this research effort -- A job shop equipped with one batch processing machine (BPM) and several unit-capacity machines has been considered. Given a set of jobs, their process routes,processing requirements, and size, the objective is to schedule the jobs such that the makespan is minimized -- The BPM can process a batch of jobs as long as its capacity is not exceeded -- The batch processing time is equal to the longest processing job in the batch -- If no batches were to be formed, the scheduling problem under study reduces to the classicaljob shop problem with makespan objective, which is known to be nondeterministic polynomial time-hard -- A network representation of the problem using disjunctive and conjunctive arcs, and a simulated annealing (SA) algorithm are proposed to solve the problem. The solution quality and run time of SA are compared with CPLEX, a commercial solver used to solve the mathematical formulation and with four dispatching rules -- Experimental study clearly highlights the advantages, in terms of solution quality and run time, of using SA to solve large-scale problems
Metaheurísticos: una alternativa para la solución de problemas combinatorios en Administración de Operaciones
(Revista EIA, 2007-12) Vélez, Mario César; Montoya, José Alejandro; Universidad EAFIT. Departamento de Ingeniería de Producción; marvelez@ eafit.edu.co; jmonto36@eafit.edu.co; Gestión de Producción y Logística
The scarce diffusion given to the newest techniques for solving complex operations management problems has as a direct consequence that companies lose opportunities to operate at lower costs and higher efficiency -- The objective of this article is to introduce and explain the fundamental ideas behind metaheuristics, a solution technique for combinatorial problems that has received the most attention from the academiccommunity in the last few years -- In order to illustrate these ideas, an example of a classical combinatorial problem in the sequencing of operations area is presented, and a solution algorithm making use of some of these techniques is proposed

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Examinando Gestión de Producción y Logística por Materia "ALGORITMOS GENÉTICOS"

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