Journal
INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH
Volume 21, Issue 2, Pages 215-246Publisher
WILEY
DOI: 10.1111/itor.12044
Keywords
job-shop; scheduling; genetic algorithm; biased random-key genetic algorithm; heuristics; random keys; graphical approach
Funding
- ERDF through the Programme COMPETE
- Portuguese Government through FTC
- Foundation for Science and Technology [PTDC/EGE-GES/117692/2010]
- Fundação para a Ciência e a Tecnologia [PTDC/EGE-GES/117692/2010] Funding Source: FCT
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This paper presents a local search, based on a new neighborhood for the job-shop scheduling problem, and its application within a biased random-key genetic algorithm. Schedules are constructed by decoding the chromosome supplied by the genetic algorithm with a procedure that generates active schedules. After an initial schedule is obtained, a local search heuristic, based on an extension of the 1956 graphical method of Akers, is applied to improve the solution. The new heuristic is tested on a set of 205 standard instances taken from the job-shop scheduling literature and compared with results obtained by other approaches. The new algorithm improved the best-known solution values for 57 instances.
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