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Next, based on the evaluation results, a new generation population of solutions is generated using three genetic operations: selection, crossover, and mutation.

An initial population of parent solutions is generated at random.

An initial population of 100 candidate solutions is generated.

A set of the most promising candidate solutions is generated to support the final decision.

In the initialization stage, a group of candidate solutions is generated randomly, called "star".

Initially, a set of solutions is generated randomly and assembled as the harmony memory (HM).

In each iteration, (l) solutions are generated.

Pareto-optimal solutions are generated using a genetic algorithm.

By applying these mechanisms, new solutions are generated.

Owing to this approach, preferable solutions are generated first.

Successive sets of solutions are generated depending upon previously generated sets.