 A multi-objective genetic algorithm for scheduling optimisation of m job families on a single machineAli Azadeh, Abbas Keramati, Afshin Karimi and Mohsen Moghaddam International Journal of Industrial and Systems Engineering, 2010, vol. 6, issue 4, 417-440 Abstract: This paper presents multi-objective scheduling of m job families on a single machine by multi-objective genetic algorithm (MOGA). We follow optimisation in three objectives: improving the tardiness, increasing the machine utilisation and decreasing the cycle time. MOGA is the combination of genetic algorithm with multi-criteria decision making. Moreover, N jobs are placed for m job families. Each job has three main distinct features including arrival time, time of processing and due date. Also, we consider setup time for each job and sequence-dependent setup time for changing jobs in different families. In order to determine the superiority of MOGA solution, we compared it with shortest processing time and earliest due date solutions. The improvement of MOGA over other approaches is shown by different cases. Keywords: multi-objective GAs; genetic algorithms; scheduling optimisation; multicriteria decision making; MCDM; sequence-dependent setup times; m job families; single machine scheduling; tardiness; machine utilisation; cycle times; arrival times; processing time; due dates. (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:ids:ijisen:v:6:y:2010:i:4:p:417-440 Access Statistics for this article More articles in International Journal of Industrial and Systems Engineering from Inderscience Enterprises Ltd |
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