Distributed scheduling problems in intelligent manufacturing systems

Distributed Manufacturing Scheduling Using Intelligent Agents

reflect the temporal relationships between manufacturing activities and the capacity limitations of a set of shared resources. The allocation also affects a schedule's opti-mality with respect to criteria such as cost, lateness, or throughput. The globalization of manufacturing makes such optimization increasingly important. To survive in this competitive market, manufacturing enterprises must ...

Intelligent Scheduling for Flexible Manufacturing Systems

A scheme for the scheduling of Flexible Manufacturing Systems (FMS) has been developed which integrates neural networks, parallel Monte-Carlo simulation, genetic algorithms. and machine learning. Modular neural networks are used to generate a small set of atlractive plans and schedules from a larger list of such plans and schedules. Parallel Monte-Carlo Simulation predicts rhe impact of each on...

On-Line Scheduling Using a Distributed Simulation Technique for Intelligent Manufacturing Systems*

On-line scheduling has traditionally been restricted to a single machine or workcell. In this paper, a distributed simulation technique for on-line scheduling is expanded to encompass several machines or workcells. Additional machines introduce several difficulties, however, the simulation better reflects scheduling demands in manufacturing environments.

Multiobjective Genetic Algorithm for Scheduling Problems in Manufacturing Systems

Scheduling is an important tool for a manufacturing system, where it can have a major impact on the productivity of a production process. In manufacturing systems, the purpose of scheduling is to minimize the production time and costs, by assigning a production facility when to make, with which staff, and on which equipment. Production scheduling aims to maximize the efficiency of the operation...

Scheduling in manufacturing systems