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- W22082767 abstract "Efficiency in job shop scheduling plays an important role when a large number of jobs and machines are considered. The job shop scheduling problems are one of the NP hard problems. Many heuristic methods give solutions with near optimal results. This work deals with the job shop scheduling using Artificial Immune System. Operation based representation is used to decode the schedule in the algorithm. The mutations used in the algorithm are inverse mutation and pair wise exchange mutation and a receptor editing process is also used. A C++ code was generated to use the algorithm for finding the optimal solution. The input parameters are operation time and operation sequence for each job in the machines provided. This work used the makespan values of the schedules to compare the results." @default.
- W22082767 created "2016-06-24" @default.
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- W22082767 date "2012-05-10" @default.
- W22082767 modified "2023-09-24" @default.
- W22082767 title "Job Shop Scheduling Using Artificial Immune System" @default.
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- W22082767 hasPublicationYear "2012" @default.
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