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A straightforward order based solution representation is applied for coding solutions of the problem and clustering approach is used to generate appropriate initial solutions.

Since solution representation is based on real numbers between 0 and 1, all generated offsprings also will be in this range and an infeasible situation does not occur (Tables 2, 3).

A simple solution representation is provided in this paper to encode the solutions.

Hardware and software based solutions are available.

The base class for point representation is RepBase.

Comparisons based on graphical representations are made between numerical and exact solutions.

This tree representation is based on a fixed-parameter tractability analysis, which is the basis for the efficient solution of the TARP.

This representation is based on 3D line segments.

The synthesis process representation is a solution candidate (individual) for the evolutionary algorithm.

This representation is considered only for the LEADSTO based formalisation.

This paper characterizes general optimization problems into four categories based on the solution representation schemes, as they have been the key to the design of various evolutionary algorithms (EAs).