Computer Scientists Achieve Breakthrough in Solving the Traveling Salesperson Problem

When Nathan Klein began his graduate studies two years ago, little did he know that he would be part of a team that would make a groundbreaking discovery in the field of theoretical computer science. Working with his advisors at the University of Washington, Anna Karlin and Shayan Oveis Gharan, Klein set out to tackle one of the most challenging problems in this field.

In a recent publication, Klein and his team have achieved what computer scientists have been striving for over the past 50 years – a more efficient method to find approximate solutions to the traveling salesperson problem. This problem involves finding the shortest or least expensive round trip through a set of cities and has wide-ranging applications, from DNA sequencing to optimizing ride-sharing logistics.

A Long-Standing Challenge

The traveling salesperson problem has captivated researchers for decades. It has not only led to fundamental advancements in computer science but has also sparked curiosity about its untapped potential. Despite numerous attempts, no algorithm has been able to efficiently find the best solutions for all possible combinations of cities.

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An Unexpected Breakthrough

Nicos Christofides made a significant contribution in 1976 with an algorithm that could efficiently find approximate solutions, with round trips at most 50% longer than the optimal route. This breakthrough was expected to be surpassed shortly after, but progress stagnated.

Karlin, Klein, and Oveis Gharan have now proven that an algorithm they developed a decade ago surpasses Christofides’ 50% factor, albeit by an infinitesimally small margin. This breakthrough not only breaks theoretical barriers but also renews hope for further advancements in solving this problem.

Traveling Salesperson

Opening New Horizons

The implications of this breakthrough are significant. It not only provides a more efficient approach to solving the traveling salesperson problem but also pushes the boundaries of what was previously thought possible. By shedding new light on the problem, researchers are hopeful that this discovery will pave the way for future breakthroughs and advancements in the field.


Q: What is the traveling salesperson problem?

A: The traveling salesperson problem involves finding the shortest or least expensive round trip through a collection of cities. It has applications in various fields, including DNA sequencing and optimizing logistics.

Q: Why is solving the traveling salesperson problem important?

A: Solving this problem has practical implications across different industries. It can lead to more efficient route planning, cost savings in transportation, and improved logistics.

Q: What is the significance of the recent breakthrough?

A: The recent breakthrough by Karlin, Klein, and Oveis Gharan offers a more efficient algorithm for finding approximate solutions to the traveling salesperson problem. This breakthrough renews hope for further advancements in this field.

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Computer scientists have made a remarkable breakthrough in their quest to solve the traveling salesperson problem. With their groundbreaking algorithm, Karlin, Klein, and Oveis Gharan have surpassed previous limitations and opened up new possibilities for finding approximate solutions. The impact of this discovery extends beyond theoretical boundaries, offering practical applications that can revolutionize industries reliant on efficient route planning and optimization. With this breakthrough, the future of the traveling salesperson problem looks promising. Click here to learn more about iBlog.

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