Operation allocation in automated manufacturing system using GA-based approach with multifidelity models

Authors:
F. T. S. Chan;A. Chaube;V. Mohan;V. Arora;M. K. Tiwari
Affiliations:
Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong, China;Department of Industrial Engineering and Management, Indian Institute of Technology, Kharagpur 834003, India;Department of Industrial Engineering and Management, Indian Institute of Technology, Kharagpur 834003, India;Department of Industrial Engineering and Management, Indian Institute of Technology, Kharagpur 834003, India;Department of Industrial Engineering and Management, Indian Institute of Technology, Kharagpur 834003, India
Venue:
Robotics and Computer-Integrated Manufacturing
Year:
2010

Citing 4
Cited 0

One-machine rescheduling heuristics with efficiency and stability as criteria

Computers and Operations Research
An Efficient Genetic Algorithm for Job Shop Scheduling Problems

Proceedings of the 6th International Conference on Genetic Algorithms
A genetic algorithm for the Flexible Job-shop Scheduling Problem

Computers and Operations Research
An integrated tool planning and production planning problem for flexible manufacturing systems using genetic algorithm

International Journal of Intelligent Systems Technologies and Applications

Quantified Score

Hi-index	0.00

Visualization

Abstract

The scheduling problem in manufacturing is considered as among the toughest to solve. The basic drawback of many proposed methods has been the huge amount of computation time for simulation. This paper proposes a framework to solve the operation allocation problem in automated manufacturing systems using the concept of multifidelity. The concept of multifidelity has been proposed by several researchers in order to reduce the computation time for simulation. In this paper, a GA-based heuristic procedure will be developed along with the multifidelity approach to solve a typical manufacturing scheduling problem. Four different fidelity models have been defined on which experimentation is carried out. The proposed method has been tested on a sample dataset and the results have been analysed to choose the fidelity model which best describes the scenario.