# A Hybrid Evolutionary Algorithm Based on Solution Merging for the Longest Arc-Preserving Common Subsequence Problem

## TL;DR

This paper introduces a hybrid evolutionary algorithm with a novel solution merging crossover operator to effectively solve the NP-hard longest arc-preserving common subsequence problem, improving upon existing heuristics.

## Contribution

It presents a new hybrid evolutionary algorithm featuring a solution merging crossover operator, demonstrating superior performance over previous heuristics for the problem.

## Key findings

- The proposed algorithm outperforms existing heuristics.
- Solution merging enhances solution quality.
- Experimental results validate the effectiveness of the approach.

## Abstract

The longest arc-preserving common subsequence problem is an NP-hard combinatorial optimization problem from the field of computational biology. This problem finds applications, in particular, in the comparison of arc-annotated Ribonucleic acid (RNA) sequences. In this work we propose a simple, hybrid evolutionary algorithm to tackle this problem. The most important feature of this algorithm concerns a crossover operator based on solution merging. In solution merging, two or more solutions to the problem are merged, and an exact technique is used to find the best solution within this union. It is experimentally shown that the proposed algorithm outperforms a heuristic from the literature.