Sentence examples for elite solution from inspiring English sources

Rank the bats and find the current best x *. t = t +1; Apply diversity and preserve elite solution.

The role of the proposed operator is to find promising solutions that share similar features with the current elite solution in the population.

In addition, local search is embedded in the CBGA after the main evolutionary search process to enhance the exploitation ability by further improving the elite solution.

Then, applying the intensification technique of the tabu search allowing to relaunch the search from an elite solution of each cluster autonomously to attain more dominant solutions of the search space.

Let E the elite solution of a cluster ({rm {CL}}_{i},) (E' in N(E)) is a neighbor of the elite solution E, ({rm{GL}}_{i}) is the global list of each ({rm{CA}}_{i}) to receive new found elite solutions by the remaining CAs, each ({rm {CL}}_{i}) plays the role of the tabu list with a dynamic length, and (C_{rm {max}}) is the makespan of the obtained solution.

This efficiency is explained by the flexible selection of the promising parts of the search space by the clustering operator after the genetic algorithm process and by applying the intensification technique of the tabu search allowing to start from an elite solution to attain new more dominant solutions.

Elite solutions are the top-ranked solutions found in each generation.

Apply a complete NM method starting from some elite solutions in the TL.  .

To further improve the performance, we introduce two novel solution search equations: the first equation incorporates the information of elite solutions and can be applied to the employed bee phase, while the second equation not only exploits the information of the elite solutions but also employs the current best solution in the onlooker bee phase.

During the environmental selection, the binary search (BS) is used to adaptively adjust the ϵ value in the ϵ-dominance relationship and assist in detecting the well-distributed neighbors for the elite solutions.

The efficiency of our approach is explained by the flexible selection of the promising parts of the search space by the clustering operator after the genetic algorithm process, and by applying the intensification technique of the tabu search allowing to restart the search from a set of elite solutions to attain new dominant scheduling solutions.