Preference-based adaptive genetic algorithm for multiobjective advanced planning and scheduling problem

Author

Yang, J. ; Tang, W.

Author_Institution

Dept. of Ind. Eng., Southeast Univ., Nanjing, China

fYear

2009

fDate

8-11 Dec. 2009

Firstpage

1935

Lastpage

1940

Abstract

In this paper, minimizing machine idle time and minimizing earliness-tardiness penalties are considered as two objectives in advanced planning and scheduling (APS). The APS problem is formulated as a mixed integer programming model. Constraints including precedence, alternative machine, capacity, and setup and transition times are taken into account. A preference-based adaptive genetic algorithm is applied to solve the model. Numerical experiments are performed to illustrate the effectiveness and efficiency of the developed algorithm.

Keywords

adaptive scheduling; adaptive systems; genetic algorithms; integer programming; machining; planning; alternative machine; mixed integer programming model; multiobjective advanced planning; preference-based adaptive genetic algorithm; scheduling problem; Collaboration; Genetic algorithms; Industrial engineering; Job shop scheduling; Lead time reduction; Linear programming; Mechanical engineering; Moon; Production; Supply chains; Adaptive genetic algorithm; advanced planning and scheduling; machine idle time; preferencebased;

fLanguage

English

Publisher

ieee

Conference_Titel

Industrial Engineering and Engineering Management, 2009. IEEM 2009. IEEE International Conference on

Conference_Location

Hong Kong

Print_ISBN

978-1-4244-4869-2

Electronic_ISBN

978-1-4244-4870-8

Type

conf

DOI

10.1109/IEEM.2009.5373213

Filename

5373213