1,720,977 research outputs found
NEPTUNE: NEw system for Probabilistic Tracking & identification of UNknown Events
No full textICAMES2001, ENSO, Bogazici University, Istanbul, Ma
Job sequencing problem in a semi-automated production process.
No full textIn this work the authors addresses the problem of sequencing a set of jobs on a single machine using a genetic algorithm and simulation. The goal is to find the schedule that minimizes the total earliness and tardiness penalties of all jobs, under the assumptions that no pre-emption of jobs is allowed and all jobs are available at time zero. In order to accelerate the search process, the Authors also implemented a procedure for genetic algorithm initialization. Simulation has been used for the fitness evaluation of the population’s members: in this way, one of the most critical issues related to evolutionary computation has been successfully addressed. This hybrid approach led to an effective tool adopted for the scheduling in a real production plant, where three bottling lines are used and several kind of product are commercialized
Warehouse layout design: minimizing travel time with a genetic and simulative approach - methodology and case study.
No full textThis paper deals with the warehouse layout optimization problem with respect to the distance reduction and the travel time minimization. The authors also searched for a flexible tool in order to optimize layout functionally to the fluctuations in demand and inventory level. The addressed optimization problem is a constrained optimization problem on an integer domain and it is shown to be NP-hard. The wide applicability of evolutionary computation and its good performances on a variety of different optimization problems have led to a strong interest in this type of algorithm. A heuristic genetic algorithm have been developed and a system for the effective assignment of the storage area to the different class of items is presented. The system is based on the association of a genetic algorithm and a deterministic simulation model.
Computational experiments are conducted to verify the effectiveness of the algorithm. They were made by applying the proposed tool to a real industrial case concerning an Italian soft drinks company.
As a result, the authors intend to provide a tool for warehouse layout and operations optimization that could be attractive for operation management researchers and realistically applicable by practitioners
A supervised multi-agent approach for APS in multi-site production systems for demand validation and evaluation
No full textA Supervised Multi-Agent Approach for APS in Multi-Site Production Systems for Demand Validation and Evaluation
No full textCompetency Needs Induced by Production Model Innovation: the starting point of BATCOS project.
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A stochastic approach to identify supply requirements, at an aircraft assembly plant, with respect to the MPS and production policies.
No full textIn this paper Authors describe the use of simulation in addressing interrelated issues such as final product due date determination, supply requirements, suppliers relationship management, work centre loading and work-in-process control in a complex assembly environment such as an aircraft firm. This is not a study focused on some improvement or creation of planning algorithms; Authors don't mean to replace existing management methodologies, such as supply or expediting practices, but to provide an high level framework in which a backward loading of the whole supply-chain is reliable. By using the stochastic approach, the main aim of this work is to analyze a complex process in order to identify and quantify the nature of the risk involved in the supply chain process, evaluating the possible consequences associated with it, since events with a low probability of occurring might generate just as unfavorable and problematic consequences on the whole final assembly process. Thus, instead of an absolutely certain result, there will be, in general, possible supply and production processes solutions, and each one has its own given probability of occurring. This application also illustrates the use of simulation for some simplified planning and scheduling needs using a system of interacting and interconnected schedulers and simulators
Strategic planning and production control: deriving an useful master production schedule from sales forecasts.
No full textThe Master Production Schedule (MPS) is the link between the strategic plan and the operative production plan. Indeed, several authors claim that MPS is one of the most important input for MRP module and detailed scheduling. In this paper the authors propose a rolling horizon MPS model for production systems with multiple production lines in presence of multiple objective functions and minimum batch-sized production lot constraints. In order to achieve long and medium term planning in a flowshop production process, the authors developed an MPS tactical planner, which schedules jobs on a horizon varying from six to ten months, considering finite capacity constraints. The planning algorithm is composed by two main procedures: the first one chooses the best heuristic by the comparison of twelve different heuristics by using production input and stochastic sales forecasts; the second one performs the scheduling of the strategic production plan by using the best heuristic previously selected and deterministic inputs. As a result the MPS is derived by using a selected heuristic starting from a stochastic comparison, even if the final production plan is obtained trough deterministic input. For these reasons we are confident that the final MPS is both robust (stochastic validation) and realistic (based on a finite capacity planning)
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