DocumentCode
2969899
Title
Combination of Genetic Algorithm and LP-metric to solve single machine bi-criteria scheduling problem
Author
Aryanezhad, M.B. ; Jabbarzadeh, A. ; Zareei, A.
Author_Institution
Dept. of Ind. Eng., Iran Univ. of Sci. & Technol., Tehran, Iran
fYear
2009
fDate
8-11 Dec. 2009
Firstpage
1915
Lastpage
1919
Abstract
This paper addresses single machine bi-criteria scheduling problem with the aim of minimizing total weighted tardiness and weighted number of tardy jobs. While weighted number of tardy jobs measures the service quality provided to customers, total weighted tardiness quantify the magnitude of lateness of each job. Therefore, considering both objectives, simultaneously, will provide the highest customers satisfaction. Both objectives are known to be NP-hard, thus, Genetic Algorithm is hired to solve the problem. Since LP-metric method is a rigorous multi-objective technique for making a combined dimensionless objective, it is used to navigate the search direction of Genetic algorithm. In this way, we can reach to some of solutions that are compatible to decision maker´s opinion while overcoming the issue of problem complexity. Finally for testing the efficiency of the proposed approach, some test problems are solved.
Keywords
computational complexity; customer satisfaction; genetic algorithms; single machine scheduling; LP metric; NP-hard problem; customers satisfaction; genetic algorithm; rigorous multi-objective technique; service quality; single machine bi-criteria scheduling problem; tardy job; total weighted tardiness minimization; Customer satisfaction; Genetic algorithms; Gold; Industrial engineering; Job shop scheduling; Navigation; Polynomials; Quality of service; Single machine scheduling; Testing; Genetic Algorithm; LP-metric;
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.2009.5373207
Filename
5373207
Link To Document