Solving JSSP by introducing Hamilton similarity and time dependent fitness scaling (CROSBI ID 165927)
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Abrashi, Arijan ; Štefanić, Nedjeljko ; Lisjak, Dragutin
engleski
Solving JSSP by introducing Hamilton similarity and time dependent fitness scaling
In this paper was proposed and tested niching genetic algorithm (GA), which for comparison of individuals in the population uses, so called Hamilton similarity. Advantage of the Hamilton similarity lies in the fact that there is no need for context sensitive information in order to successfully compare two population members. Furthermore, the algorithm was tested on the famous Job Shop Scheduling Problem (JSSP) - benchmark mt10, and statistical results of the test were given. In addition to the Hamilton similarity, time dependent fitness scaling was proposed which in conjunction with niching significantly reduces the probability of the algorithm to get stuck in one of the less desirable local optimum. Finally, suggestions for the future research are given.
genetic algorithm; niching; Hamilton similarity; time dependent fitness scaling
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