Optimal Stochastic Production Scheduling for Uncertain Re-entrant Assembly Workshops

DOI

10.2991/iccmcee-15.2015.82How to use a DOI?

Keywords

Uncertain Re-entrant; Production Scheduling; Genetic Simulated Annealing Algorithm.

Abstract

An optimal stochastic problem of production scheduling for uncertain re-entrant assembly workshops (URAWs) was studied, in which the assembly process is repeated on the basis of quality inspection result and the number of repeats is uncertain. According to analysis of URAWs, a stochastic expected value model of production scheduling was built up. In order to solve the model conveniently, the model was then converted into a deterministic model. A genetic simulated annealing algorithm based on feasible region (FR-GSAA) was designed to solve this model. Finally the result of simulation examples indicates that the model and the algorithm are feasible and practical.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - NanYun Jiang
AU  - Hongsen Yan
PY  - 2015/11
DA  - 2015/11
TI  - Optimal Stochastic Production Scheduling for Uncertain Re-entrant Assembly Workshops
BT  - Proceedings of the 2015 4th International Conference on Computer, Mechatronics, Control and Electronic Engineering
PB  - Atlantis Press
SP  - 428
EP  - 433
SN  - 2352-5401
UR  - https://doi.org/10.2991/iccmcee-15.2015.82
DO  - 10.2991/iccmcee-15.2015.82
ID  - Jiang2015/11
ER  -