In this paper, the effectiveness of the genetic operations of thecommon genetic algorithms, such as crossover and mutation, are analyzedfor small search range situations. As expected, the thus-obtainedefficiency/performance of the genetic operations is quite different fromthat of their large search range counterparts. To fill this gap, alightweight genetic search algorithm is presented to provide anefficient way for generating near-optimal solutions for these kinds ofapplications
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