Abstract
A new radial memetic algorithm is proposed to resolve the no-wait job-shop scheduling problem. Basically, each sequencing solution is factorized as a distance-based ranking model, i.e., each solution is decomposed in n − 1 terms, where n is the number of jobs to be sequenced. After that, a cumulative radial distribution of hydrogen is considered to produce new factorizations using the offspring information (genes). Such radial distribution is applied in the local optimization procedure of the memetic algorithm. A benchmarking dataset is used to show the performance of this new experimental technique, as well as other current procedures. Statistical tests were implemented to confirm the performance of the proposed scheme.
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