Exact(4)
The variation operators were designed with particular emphasis on low computational effort and strong locality.
To solve the job shop scheduling problem more effectively, some genetic operators were designed in this paper.
To solve the proposed model more effectively, some tailor made genetic operators were designed by making full use of the characteristics of the problem.
Two efficient genetic operators were designed for searching in a feasible solution space and obtaining neighborhood solution, as follows: 1) Crossover operator: This operator randomly selects two different routes of two vehicles of the feasible solution.
Similar(56)
Moreover, special inter-grid transfer operators are designed.
Different corresponding operators are designed in the methodology.
Also some granular evolutionary operators are designed for classification problem.
These two operators are designed by studying two forms of local convergence.
The scalar operators are designed to enhance the population diversity and avoid premature convergence.
In the genetic algorithm, tailor-made crossover, mutation and local search operators are designed.
In addition, the learning operators are designed to enhance the global and local search ability.
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