travelling salesman terraria

Shadows Over Loathing

Traveling Merchant

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5 Update Info

Defense [ ]

Shoots at enemies with a Revolver. (Pre-Hardmode)

Fires off the Pulse Bow at nearby enemies. (Hardmode)

Weapons/Tools
Armors/Vanities
Accessories
Paintings/Furniture
Materials/Potions
When the Traveling Merchant leaves after his one day cycle it will say "The Traveling Merchant has departed!" in the chatbox.
If you log out of the game while the Traveling Merchant is there, he will be gone when you log back in even though it is still the same day.
The Traveling Merchant won't depart if the player can see him and will only depart if he goes offscreen.
Sometimes he spawns outside the inhabited area and gets killed off-screen, resulting in the game informing you that "<Traveling Merchant name> was slain."
Instead of leaving directly at night (7:30PM), he leaves at 6:00PM. The same applies for mornings: he can appear between 4:30AM and 12:00PM.
The reason that the Traveling Merchant has different items to be purchased might be that he goes to different regions around the world every time he leaves.
His hat with a feather may be a reference to Hermes , the Greek god of merchants, thieves, and travelers.
"Combination hookah, coffee maker and makes julienne fries" is a line from the Disney film Aladdin.

Update Info [ ]

Now sells Sitting Duck's Fishing Pole.
Now correctly summoned to King Statue .
Added to the game.
1 Vile Powder
2 Heart Statue
3 Angel Wings

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Items Traveling Merchant Summon Item

Thread starter Chweemy
Start date Sep 2, 2023
Terraria - Discussion
Game Suggestions

Sep 2, 2023

I'm sure we've all been there waiting for the traveling merchant to travel to us, just to not have the item we needed. Causing you to wait several more days for another one just for a chance to get the merchant to sell you the item you need again. Recently the Peddler's Satchel has helped this process by adding another item to the merchant's inventory, but that's just one Band-Aid fix to the RNG problem. So I devised the idea that there be an item to "attract" a traveling merchant to your world. Similar to how the Goblin Battle Standard works by summoning the army to approach, I think an item that could force the merchant to appear the following day, or that day if there's not already a merchant, would combat the issues of hoping for RNG's favor. I'm not the most creative with designing items like these, but there have been several symbols or symbolic items or ideas that represented commerce throughout world history that could server as inspiration for item design such as symbols of the Greek God Hermes or a Merchant's Mark/Emblem.

Fluffydot473

Or, Make the Traveling Merchant move in.

Fluffydot473 said: Or, Make the Traveling Merchant move in. Click to expand...

Since the Traveling Merchant likes exotic goods he could have an increased chance of showing up the day after you turn in a Strange Plant to the Dye Trader

Heath04🌳 said: Since the Traveling Merchant likes exotic goods he could have an increased chance of showing up the day after you turn in a Strange Plant to the Dye Trader Click to expand...

Chweemy said: an unexplained method that would lead to most players not knowing that exist. Click to expand...

Heath04🌳 said: Well for a while I've been advocating for a better NPC system that doesn't require just asking the Guide's help for everything, this can also work by just adding some dialogue to the Dye Trader/a better tooltip on the Strange Plant Click to expand...

Yousef the H

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Cavern NPCs
Passive AI NPCs

Skeleton Merchant

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Internal NPC ID : 453

A Skeleton Merchant found lurking in the Cavern .

The Skeleton Merchant is an NPC vendor that randomly spawns in the Cavern layer .

He is not a Town NPC and will despawn when off-screen, although enemies will not spawn near him.

The Skeleton Merchant's stock changes at dawn (4:30 AM) daily, and he does not need to respawn for it to do so. The majority of the items in his inventory will vary, depending on the current moon phase .

He will throw Bones to fend off nearby non-skeletal enemies, while ignoring bosses and most other skeletons.

Unlike other NPCs, the Skeleton Merchant does not have a map icon. A Hunter Potion will highlight him.

He is one of the few entities that can be detected by the Lifeform Analyzer or its upgrades. His current name will be displayed (e.g. Rattles Magoo) rather than Skeleton Merchant .

1 Items sold
2 Shimmered form

Items sold [ ]

Shimmered form [ ].

When submerged in Shimmer , the Skeleton Merchant will transform into his Shimmered form. This has no impact on gameplay or dialogue and is only a visual change. He can be returned to his classic look by submerging him in Shimmer again.

The Skeleton Merchant may have any of the following names:

Billy Marrows
Bones McGee
Gloomy Mays
Jack Sellington
Mandible Calavera
No-Eyed Wiley
Rattles Magoo
Skellington
He cannot be teleported by the Portal Gun or King Statue .
He can sometimes spawn in pools of water . However, his skeletal nature renders him immune to drowning.
He will not attack bosses same for Skeletron. He may still be damaged by them, however.
He cannot be killed by explosives deployed by the player. However, he may spawn in front of a Detonator or pressure plate explosive trap. Because of his bulkier appearance, players interacting with him may unwillingly hit the plunger on the detonator trap, killing both him and the player.
This may not apply to 1.4 – needs further testing ( Expert Spider Caves still spawn Black Recluses when the Skeleton Merchant is in the safe box, at least).
If the Skeleton Merchant is nearby, Bunnies can spawn underground.
He does not spawn on jungle grass or corrupted blocks.
His shimmered appearance resembles a zombified version of himself with fancier clothing.
If the Skeleton Merchant walks into Shimmer, his sprite changes into a zombified old man with a beard.
Selling items to him can help a player clear out their inventory in the middle of a long caving session.
If a player notices a Bunny in the Caverns, or a suspiciously low number of enemies on their Radar , it could be a sign that the Skeleton Merchant has spawned.
The names Jack Sellington and Skellington are references to Jack Skellington from the 1993 American animated fantasy Halloween/Christmas film The Nightmare Before Christmas .

The Skeleton Merchant's scavenging animation

The name "Bones McGee" is a reference to Leonard H. "Bones" McCoy , a character in the American science fiction franchise Star Trek .
The name "No-Eyed Wiley" is a reference to One-Eyed Willy from the 1985 American adventure comedy film The Goonies .
The name "Mandible Calavera" is a reference to Manuel "Manny" Calavera from the adventure game Grim Fandango .
The names "Billy Marrows" and "Gloomy Mays" are a reference to the late American television salesperson Billy Mays .
"Tom" may also be a reference to the enemy Tim .
The quote about Slime Oil is a reference to the " miracle medicine " peddlers of the 1800s, who were commonly called Snake Oil Salesmen.
The quote " The only things constant in this world are death and taxes, I've got both! " is a reference to Benjamin Franklin 's famous quote: "In this world, nothing can be said to be certain, except death and taxes."
The quote " You would not believe some of the things people throw at me... Wanna buy some of it? " is a reference to a young scavenger named Squirt the Peddler in the action role-playing game Diablo III . Squirt periodically asks the player a near-exact variation of this question, but refers to "things people throw away" instead of "things people throw at me".
The quote " Stay away from the spiders. They'll suck out your insides and leave you a hollow shell of a man. Trust me on this one. " suggests that he came to be after being killed by a Spider.
Even though he is not a town NPC, he will throw confetti during a Party .
He is one of two NPCs that does not have a map icon, the other being the Old Man .
He is the only NPC that always despawns once off-screen. The Traveling Merchant also despawns when off-screen, but only after 6:00 PM.
Despite the fact one of his quotes makes a joke on the idea, the Skeleton Merchant does not sell Maggots .
If the Skeleton Merchant is slain, no message pops up to announce his death, unlike most NPCs.
The counterweights he sells resemble dice used in Dungeons & Dragons . This is a possible reference to weighted dies used for cheating, which may be provided by a disreputable merchant such as the Skeleton Merchant.

History [ ]

Desktop 1.4.0.4 : Fixed Traveling Merchant and Skeleton Merchant accidentally having NPC Happiness .
Desktop 1.4.0.1 : Now shows its name in the Lifeform Analyzer rather than "Skeleton Merchant".
Desktop 1.3.1 : Now has a chance to be named "Mika".
Desktop 1.3.0.1 : Introduced.

Switch 1.0.711.6 : Introduced.

Mobile 1.3.0.7 : Introduced.

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Solving the Traveling Salesman Problem

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Enter your stops, optimize your routes, manage your team – quickly and efficiently.

Imagine a salesman who needs to visit multiple cities, but he wants to minimize the distance traveled and return to the starting point. This classic problem, known as the Traveling Salesman Problem (TSP), has been a subject of study for over a century. The applications of TSP are widespread, from logistics and agriculture to astronomy and computer-generated art. In this blog post, we will delve into the world of the Traveling Salesman Problem, exploring its history, algorithms, and real-world applications.

Short Summary

The Traveling Salesman Problem is a complex problem of finding an optimal route for a round trip.
Solutions to the TSP include NP-hard classification, brute force approach, dynamic programming and Christofides’ Algorithm.
Route planning software such as OptimoRoute provide businesses with efficient tools for tackling the TSP, thereby improving their operations and saving resources.

Understanding the Traveling Salesman Problem

The Traveling Salesman Problem (TSP) is a problem of determining the most efficient route for a round trip, with the objective of maintaining the minimum cost and distance traveled. It serves as a foundational problem to test the limits of efficient computation in theoretical computer science.

The salesman’s objective in the TSP is to find a minimum weight Hamiltonian cycle, which maintains both the travel costs and the distance traveled at a minimum.

Theoretical Background

The TSP is classified as an NP-hard problem. This shows that the number of solution sequences grows rapidly with the number of cities. The brute force approach to resolving the TSP involves examining each round-trip route to ascertain the shortest one. However, as the number of cities increases, the number of round-trips to check can quickly surpass the capability of the most powerful computers. This limitation has led to the development of more sophisticated algorithms to tackle the TSP, such as dynamic programming and approximation algorithms.

The Hamiltonian Cycle Problem, also known as the Hamiltonian cycle problem, inquires whether there exists a closed walk in a graph that visits each vertex precisely once and is closely related to the TSP. Both problems have been studied extensively by computer scientists due to their implications in complexity theory and the P versus NP problem.

Optimal vs. Approximate Solutions

In solving the TSP, there is a distinction between optimal solutions and approximate solutions. Optimal solutions are the most advantageous route, while approximate solutions are round-trip routes whose lengths approach that of the most advantageous route. The brute force approach involves determining every potential solution and subsequently selecting the most advantageous one. However, this method is computationally intractable for large TSP instances.

One notable approximate solution is Christofides’ algorithm, which begins by determining the shortest spanning tree and subsequently converting it into a round-trip route. This algorithm guarantees a response that is, at most, 1.5 times the optimal solution. While not always yielding the optimal solution, approximate algorithms like Christofides’ algorithm provide a more feasible approach to solving the TSP.

Evolution of TSP Algorithms

TSP algorithms have been in existence since the 1950s, when the initial brute force approach was formulated. Subsequently, more sophisticated techniques such as dynamic programming and Christofides’ algorithm have been developed. These advanced algorithms have enabled researchers and practitioners to find near-optimal solutions to the TSP more quickly and efficiently.

By leveraging these algorithms, it is possible to solve the TSP in a fraction of the time.

Brute Force Approach

The brute force approach to TSP involves attempting all potential solutions, making it the most time-consuming and expensive method. As the number of destinations increases, the number of roundtrips likewise increases exponentially, rendering it computationally intractable even for the most powerful computers. Therefore, the brute force approach is not considered to be a viable solution for large TSP instances.

Despite its limitations, the brute force approach serves an important role in the history of TSP algorithms. It represents the initial attempt to solve the TSP and laid the groundwork for the development of more advanced and efficient algorithms.

Dynamic Programming

Dynamic programming is a technique employed to address intricate issues by segmenting them into more manageable subproblems and resolving them one at a time. It is regularly utilized to resolve the Traveling Salesman Problem due to its ability to avoid redundant calculations and identify the shortest route that visits all cities exactly once. The dynamic programming approach is more scalable than the brute force approach, as it can be employed to solve problems of any size.

However, dynamic programming is not without its limitations. It can be computationally expensive and time-consuming, as it necessitates solving a substantial number of subproblems. Despite these drawbacks, dynamic programming remains a popular and effective method for solving the TSP.

Christofides’ Algorithm

Christofides’ algorithm is an algorithm for obtaining approximate solutions to the Traveling Salesman Problem. It involves constructing a minimum spanning tree and then discovering a minimum-weight perfect matching on the odd-degree vertices of the tree. This algorithm, developed in the 1970s, utilizes a combination of graph theory and heuristics to address the TSP.

The significance of Christofides’ algorithm lies in its ability to yield routes that are guaranteed to be no more than 50 percent longer than the shortest route. While it may not always provide the optimal solution, its development marked a substantial improvement in the pursuit of efficient TSP algorithms.

Recent Advances in TSP Algorithms

In recent years, computer scientists have made significant advancements in TSP algorithms. These breakthroughs include:

Approximation algorithms
Metaheuristic approaches
Local search operators
Anytime Automatic Algorithm Selection

These cutting-edge algorithms have enabled researchers to find even more efficient solutions to the TSP, further demonstrating the importance of continued research and development in this area.

Geometry of Polynomials

Oveis Gharan and Nathan Klein used the geometry of polynomials approach to solve the TSP by representing the problem as a polynomial with variables corresponding to the edges between all the cities. This approach permits the utilization of geometric techniques and algorithms to discover an optimal or approximate solution to the problem, including determining the starting and ending point of the route.

This innovative method showcases the potential for leveraging mathematical techniques and geometrical properties in solving the TSP. As research progresses, it is expected that even more efficient algorithms and approaches will be developed, further pushing the boundaries of our understanding of the TSP.

Fractional Solutions and Rounding Techniques

Amin Saberi and Arash Asadpour developed a general rounding technique that employs randomness in an attempt to select a whole-number solution that preserves as many characteristics of the fractional solution as possible. The use of fractional solutions and rounding techniques can be utilized to construct effective approximation algorithms for the TSP.

Saberi, Gharan, and Singh implemented this general rounding technique to formulate a new approximation algorithm for the TSP. As computer scientists continue to explore new approaches and techniques, it is likely that even more powerful and efficient algorithms will be developed to tackle the complex TSP.

Practical Applications of TSP Solutions

TSP solutions are employed in a variety of industries, including logistics, astronomy, agriculture, and vehicle routing. Its applications range from planning efficient delivery routes and optimizing telescope trajectories to designing microchips and creating computer-generated art.

The widespread use of TSP solutions underscores the importance of continued research and development in this area, as advancements in TSP algorithms have the potential to positively impact numerous sectors.

Route Optimization

Route optimization is the process of determining the most efficient routes for various applications. In logistics, for example, TSP solutions can assist in enhancing efficiency in the last mile. By employing optimization techniques, businesses can reduce the number of stops, minimize total distance traveled, and ultimately save on fuel and labor costs.

The Vehicle Routing Problem (VRP), a generalized form of the TSP, focuses on discovering the most efficient set of routes or paths for multiple vehicles and hundreds of delivery locations. By utilizing TSP solutions and optimization techniques, companies can greatly improve their overall efficiency and productivity, leading to significant cost savings and improved customer service.

Last-Mile Delivery Challenges

The last-mile delivery problem refers to the final stage of a supply chain. It involves transporting goods from a transportation hub, such as a depot or warehouse, to the ultimate recipient. TSP solutions play a crucial role in addressing this challenge by optimizing delivery routes, reducing the number of stops, and minimizing total distance traveled.

For example, the Traveling Salesman Problem with Time Windows (TSPTW) approach considers specific time constraints for each delivery location, ensuring that deliveries are made within a specified time frame. By employing TSP algorithms and optimization techniques, businesses can:

Overcome last-mile delivery challenges
Improve overall efficiency
Achieve cost savings
Enhance customer satisfaction

TSP Solvers for Real-World Problems

Modern TSP solvers use advanced algorithms to provide near-optimal solutions quickly. These solvers include the routingpy library, real-life TSP and VRP solvers, and state-of-the-art TSP solvers based on local search.

By leveraging these powerful algorithms, businesses and researchers can tackle real-world TSP problems with greater efficiency and accuracy.

Branch and Bound Method

The branch and bound method is an algorithm utilized to address optimization problems, such as the TSP. It functions by exhaustively examining all potential solutions and identifying the most advantageous one. By dividing the problem into smaller subproblems and determining the optimal solution for each subproblem, the branch and bound method permits a more efficient and precise resolution to the problem.

Although the branch and bound method is computationally expensive, it has several advantages, such as being relatively straightforward to implement and capable of addressing large-scale problems. Its application in solving real-life TSP instances showcases its potential in effectively optimizing routes and minimizing costs.

Nearest Neighbor Method

The Nearest Neighbor algorithm is a greedy algorithm that finds the closest unvisited node and adds it to the sequencing until all nodes are included in the tour. While it rarely yields the optimal solution, particularly for large and intricate instances, it can be utilized effectively as a means to generate an initial feasible solution quickly.

This initial solution can then be supplied into a more sophisticated local search algorithm for further optimization. The Nearest Neighbor algorithm demonstrates that even relatively simple algorithms can play a valuable role in providing quick and feasible solutions to real-world TSP problems.

Route Planning Software for TSP

Utilizing route planning software to solve TSP problems in various industries offers numerous benefits. These software solutions, such as Route4Me, leverage advanced algorithms like Dijkstra’s Algorithm to quickly identify the most efficient route for a team.

By implementing route planning software, businesses can improve efficiency, reduce costs, and enhance customer satisfaction.

Advantages of Route Planning Software

Route planning software can help businesses in the following ways:

Optimize routes
Decrease the number of stops
Minimize the total distance traveled
Increase efficiency and productivity
Reduce fuel and labor costs by optimizing routes and minimizing the time spent on route planning and decision-making.

Improved customer service is another benefit of route planning software. By optimizing routes and ensuring timely deliveries, businesses can enhance their reputation and build customer loyalty. In an increasingly competitive market, utilizing route planning software can give businesses a critical edge in delivering exceptional service and maintaining customer satisfaction.

Examples of Route Planning Solutions

There are numerous route planning solutions available for addressing the TSP, including vehicle routing software, optimization algorithms, and Excel sheets with order details and addresses. These solutions offer businesses a variety of options to choose from, depending on their specific needs and requirements.

Some examples of popular route planning software include OptimoRoute and Straightaway. These software solutions can help businesses tackle TSP problems efficiently, saving time and resources while improving overall operations. By leveraging advanced algorithms and powerful tools, route planning software provides a valuable solution for businesses looking to optimize their logistics and delivery processes.

Throughout this blog post, we have explored the fascinating world of the Traveling Salesman Problem, delving into its history, algorithms, and practical applications. From the early brute force approach to modern approximation algorithms and route planning software, the TSP continues to challenge and inspire researchers, computer scientists, and businesses alike. As we continue to push the boundaries of our understanding of the TSP, the potential for new and innovative solutions to real-world problems remains vast and exciting.

Frequently Asked Questions

Has anyone solved the traveling salesman problem.

No one has successfully come up with an algorithm to efficiently solve every traveling salesman problem, despite notable progress being made over the years.

What is the Traveling Salesman Problem (TSP)?

The Traveling Salesman Problem is an optimization problem that seeks to determine the most efficient route for a round trip, with the aim of minimizing cost and distance traveled.

What are some examples of industries that benefit from TSP solutions?

TSP solutions are widely used in industries such as logistics, astronomy, agriculture, and vehicle routing, providing a range of benefits.

What is the difference between optimal and approximate solutions in TSP?

Optimal solutions in TSP provide the most advantageous route, while approximate solutions offer a similar route whose length is close to that of the optimal solution.

These solutions can be used to solve a variety of problems, such as finding the shortest route between two cities or the most efficient way to deliver goods. They can also be used to optimize the use of resources, such as time and money.

What is an example of a modern TSP solver?

Routingpy is an example of a modern TSP solver, providing comprehensive tools to address the Traveling Salesman Problem and Vehicle Routing Problem.

It offers a range of features, including an intuitive user interface, fast computation times, and a wide range of optimization algorithms. It also provides a comprehensive set of tools for analyzing and visualizing the results of the optimization process.

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Skeleton merchant.

Internal NPC ID : 453
Internal Projectile ID : 21

“ You would not believe some of the things people throw at me... Wanna buy some of it? — The Skeleton Merchant

The Skeleton Merchant is an NPC vendor that randomly spawns in the Cavern layer . He is not a town NPC and will despawn when off-screen, although enemies will not spawn near him.

He will throw Bones to fend off nearby non-skeletal enemies, while ignoring most other skeletons.

Unlike other NPCs, the Skeleton Merchant does not have a map icon.