# An Efficient Information Retrieval System Using Evolutionary Algorithms
## 3 Methodology
### Advanced Document Indexing Method (ADIM) Stage
#### 3.1.2 Adim
The second method is called tournament selection; this method involves choosing a set of individuals randomly from the population. The third method is the truncation selection of this type with a threshold and fraction of the best individuals selected. The fourth method is thegenitor selection; this method works individual by individual during the selection of offspring for birth according to linear ranking and selection of the current worst individual to replace. The privilege of the simple random sampling method is over-proportional selection; it allows some weaker solutions to survive in the process of selection. The solutions may include some components, which could prove the usefulness of recombination. Furthermore, truncation selection may stick at local optima and cannot converge from initially selected chromosomes. Finally, the elitism method is used in the MGA by the process of parent selection. This means the best individual copies in the next generation; this technique allows only strong individuals to participate in the process of the generation of solutions, preventing weak individuals. The best individuals have maximum fitness. This improves the GA performance increasingly. ### Crossover Operator (Single-Point)

A simple and adequate single-point crossover is used in this proposed system to exchange the right part of the first chromosome with the right part of the second chromosome, starting with determining the cross-point (CP) value, which is calculated in Equation (4). CP splits the chromosome into two parts (left and right), then examines each gene on the first chromosome with the genes on the second chromosome. If this gene is the same one on the second, it stays on the first chromosome and does not exchange. However, if the gene is not found on the second chromosome, it can be exchanged with the second gene, and accordingly for the other genes. Ultimately, fitness values can be increased or decreased according to gene exchange. Algorithm 4 illustrates the proposed single-point crossover operation. Figure 6 depicts an example of the crossover operator. \[\text{Cross-point (CP)}=\text{length of chromosome}/2 \tag{4}\]

### Mutation Operator

To avoid local convergence, the mutation is implemented with a tiny probability (1% in the presented work). In mutation, one gene is selected randomly from the generated offspring and replaced with one from the search space. Figure 7 demonstrates this operator. ### Stopping Criteria

The MGA operation is repetitive. Every iteration has a generation, consisting of a solution group of chromosomes. The iteration number was 15. Thus, the stopping criteria were either MGA with 15 iterations or lacking solution enhancement. The achieved enhancement was measured based on the predefined FF. Accordingly, it was lacking in accuracy enhancement. For enhancement, we assumed a threshold of 0.05 to measure the

Figure 6: Crossover operator representation. Figure 7: Mutation operator representation. difference in accuracy between two consecutive generations; whenever the difference is less, the process stops. #### 3.3.2 Culture Algorithm (MCA)

After the MGA has generated the initial population, the CA uses the training set for the adaptation process to achieve high-performance results. Algorithm 5 depicts the details of this algorithm. ### GA and CA Integration

We apply the ADIM (the preprocessing stage is explained later in Section 3.1), QSA (query search algorithm explained in Section 3.2), and evolutionary algorithms. MGA is used to select the best chromosome, as the data consist of high-dimensional features with seven different classes that are used to extract the prepared data. If the fitness function percentage is not acceptable, it affects the CA parameters, changing them and calculating a new accuracy. What is meant by not being accepted is that the accuracy is less than the threshold. For this work, the threshold was set to the minimum accuracy achieved by other researchers, which was 90.31% [40].