DocumentCode :
3242699
Title :
Genetic algorithm for solving total weighted tardiness and sum of earliness and tardiness penalties of job-shop scheduling problem
Author :
Omar, Mohamed K. ; Anuar, Nurul Izah Bt ; Supaya, Yasothei
Author_Institution :
Bus. Sch. - Malaysia, Nottingham Univ., Semenyih, Malaysia
fYear :
2011
fDate :
19-21 April 2011
Firstpage :
1
Lastpage :
6
Abstract :
This paper addresses a scheduling problem known in the job-shop industrial environment and recommends solving the problem using the Microsoft Excel spreadsheet and an add-in that provides Genetic Algorithm which is capable of solving complex scheduling problems. The authors selected total weighted tardiness and sum of earliness and tardiness penalties as performance measures to determine the quality of the solution. The contribution of this paper is the fact that it demonstrates to the practitioners involved in complex scheduling problems that Microsoft Excel, which is mostly used as spreadsheet software, with appropriate add-ins can be used to solve such complex scheduling problems. Moreover, the paper uses a job-shop benchmark instance available in the OR-Library with some modification to show the capability of the proposed approach.
Keywords :
genetic algorithms; job shop scheduling; Microsoft Excel spreadsheet; OR-Library; earliness penalties; genetic algorithm; job-shop industrial environment; job-shop scheduling problem; tardiness penalties; total weighted tardiness; Genetic algorithms; Job shop scheduling; Particle measurements; Processor scheduling; Spreadsheet programs;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Modeling, Simulation and Applied Optimization (ICMSAO), 2011 4th International Conference on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-1-4577-0003-3
Type :
conf
DOI :
10.1109/ICMSAO.2011.5775549
Filename :
5775549
Link To Document :
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