# Random-Key Cuckoo Search for the Travelling Salesman Problem

arXiv: https://arxiv.org/abs/1607.04324 · HTML: https://mlsanity.com/paper/1607.04324/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 14 Apr 2016.

## Built on by (most cited first, 3 of 3)

- [Visual Reasoning and Multi-Agent Approach in Multimodal Large Language Models (MLLMs): Solving TSP and mTSP Combinatorial Challenges](https://mlsanity.com/paper/2407.00092/) (2024)
- [Metaheuristics for (Variable-Size) Mixed Optimization Problems: A Unified Taxonomy and Survey](https://mlsanity.com/paper/2401.03880/) (2024)
- [A Random-Key Optimizer for Combinatorial Optimization](https://mlsanity.com/paper/2411.04293/) (2024)

## Abstract (arXiv)

Combinatorial optimization problems are typically NP-hard, and thus very challenging to solve. In this paper, we present the random key cuckoo search (RKCS) algorithm for solving the famous Travelling Salesman Problem (TSP). We used a simplified random-key encoding scheme to pass from a continuous space (real numbers) to a combinatorial space. We also consider the displacement of a solution in both spaces using Levy flights. The performance of the proposed RKCS is tested against a set of benchmarks of symmetric TSP from the well-known TSPLIB library. The results of the tests show that RKCS is superior to some other metaheuristic algorithms.