Home Stories What Is The Travelling Salesperson Problem, And How Is It Solved?

What Is The Travelling Salesperson Problem, And How Is It Solved?

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The traveling salesperson problem (TSP) is common amongst the delivery riding business. As someone who caters to many customer’s needs, delivery riders often encounter the dilemma of figuring out the shortest yet the most convenient route during deliveries with more than one destination. In business, the more orders delivered, the better. So, riders often get stressed out finding the “best” route to take.

There are quite a few approaches mathematicians and scientists formulated to solve the traveling salesman problem. This caught the attention of the academy because of its odd placement. Experts even described it as something so easy to look at yet so challenging to solve. 

Don’t worry about going through the troubles of solving it from scratch, though. We have listed below some of the most common solutions formulated to overcome the long-standing predicament of the traveling salesperson problem (TSP).

1.Use route optimization algorithms.

Not every business owner has the ability and the time to formulate their algorithms, of course. That is why we recommend that they install an online route planner that can create an accurate algorithm for them, optimize their drivers’ routes within seconds, and save them from going through inconveniences. There are many accessible route planning applications out there that offer quality service at such an affordable price. 

Apps like Route4me, MapQuest, and Routesavvy are one of the highly used route planning services right now, so you can take a look at them and try to find the one that would suit well with your taste and with your business. Start investing in route planning applications and observe how much time and profit you will make. There’ll be no more traveling salesperson problems for even multiple routes within a few clicks.

2.Try using the Nearest Neighbor Method.

The Nearest Neighbor Method suggests that to avoid experiencing TSP, drivers should always go to the nearest destinations first before going to the more complicated ones. Other riders believe that deliveries with farther locations should be accommodated first, and they can just go back and deliver the nearer deliveries. 

This thinking causes confusion and wasted time because the riders will pass by the nearby customers when they could deliver it right away. After the farthest delivery is completed, riders will return to the customers he passed by to give them their products. Can you imagine the amount of time he had wasted just from going back and forth?

That is why experts suggest using the Nearest Neighbor Method. Start delivering from the nearest area and progress to the more faraway ones. No time will be wasted, and deliveries will be more efficient.

3.If you have more time, use the Brute-Force Approach.

This solving approach is also known as the “Naive Approach.” Well, from its name, this approach is for those who want to create their algorithm and formulate their routes manually. 

This is advisable for business owners who want to understand how to deliver business in a more in-depth manner. To do so, one will determine all the possible routes a driver can take on each delivery, compute the estimated travel time they will take on each way, and compare it to one another. After computation, the one that resulted in being the shortest and most efficient route should be the perfect route a driver can take for a wiser delivery.

This approach is best in determining the shortest route. So, if you make nearby deliveries, the computations might not be that complex, and this approach will be perfect to use.

The Travelling Salesperson Problem is a dilemma that might stress out your riders, and truthfully, it can happen anytime. Fortunately, with the rise of science and technology, solving this difficulty isn’t as hard as before. With formulas made by academic experts, this problem will only be a bump in the road, and riders will continue to make accurate, fast, and convenient deliveries.

David Smith
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