An extended Akers graphical method with a biased random-key genetic algorithm for job-shop scheduling
نویسندگان
چکیده
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 graphical method of Akers (1956), 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.
منابع مشابه
A Biased Random-key Genetic Algorithm for Job-shop Scheduling
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...
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ورودعنوان ژورنال:
- ITOR
دوره 21 شماره
صفحات -
تاریخ انتشار 2014