Understanding the Importance of Shortest Route Determination

Oct 13, 2025 by magicalceylontours.com 105 views

# Determination of the Shortest Route: Comparison of Local Beam Search Algorithm and Floyd-Warshall Algorithm in Deli Serdang

Introduction

Deli Serdang, a district located in North Sumatra, is known for its amazing natural beauty and rich historic sites. This area offers a variety of tourist destinations, ranging from beach tourism, nature tourism, to historical tourism, which attracts the attention of both local and foreign tourists. However, with the many choices of tourist attractions available, it is essential for tourists to have an efficient travel route. Therefore, the determination of the shortest route between various tourist attractions is the key to facilitating travel, saving time, energy, and costs.

Understanding the Importance of Shortest Route Determination

In the context of tourism, the shortest route determination is crucial for several reasons. Firstly, it enables tourists to plan their itinerary efficiently, allowing them to visit multiple attractions within a limited time frame. Secondly, it helps to reduce travel time and energy expenditure, making the overall tourist experience more enjoyable. Lastly, it contributes to the overall economic benefits of tourism, as tourists are more likely to spend money on local services and products when they have a well-planned itinerary.

Local Beam Search Algorithm: A Quick but Not Always Optimal Solution

Local Beam Search, as one of the Hill Climbing techniques, works by finding the best point around the current location by comparing all the closest points. This allows tourists to choose the best attractions on the path that is being taken. The algorithm has a trip time of 478.8 ms and the complexity of the algorithm θ (n^3) in testing 5 points, offering a fairly good speed in identifying efficient routes. The main advantage is the ability to filter choices quickly and focus on the nearest area, making it ideal for situations where decisions are quickly needed.

However, local beam search also has limitations, which is the possibility of being trapped in local solutions that are not optimal. That is, although fast, this algorithm does not always guarantee the best results in all conditions, especially if there are many alternative pathways that are better but not directly detected.

Floyd-Warshall Algorithm: A More Comprehensive but Slower Solution

The Floyd-Warshall algorithm is searching by comparing the current location with all the neighboring points, then choosing the closest point to the final destination. This algorithm has the execution time of 596.55 MS in the same test and complexity that is also θ (n^3), providing guarantees to find the shortest path even though it may take longer than local beam search. This algorithm is more suitable for more complex problems with many connected points, because it evaluates all possible paths in one process.

Comparison of Local Beam Search and Floyd-Warshall Algorithm

When applied to the context of tourism in Deli Serdang, the selection between the two algorithms can be guided by certain factors, such as the number of tourist attractions you want to visit, the time limit of travel, and the needs of visitors. If tourists want to travel quickly to some of the closest places, local beam search may be a better choice. However, if the focus is on the optimization of the most efficient route to reach many destinations, Floyd-Warshall can provide more satisfying results.

Case Study: Tourism in Deli Serdang

In the context of tourism in Deli Serdang, the application of local beam search and Floyd-Warshall algorithm can be seen as a way to improve the tourist experience. By utilizing these algorithms, tourists can take advantage of technology in their travel planning, making it easier to navigate the area and visit multiple attractions. Each algorithm has different characteristics, which allows visitors to choose according to their needs and preferences.

Conclusion

In planning a trip in Deli Serdang, tourists are faced with the importance of choosing the shortest route to improve their tourist experience. By utilizing the local beam search and Floyd-Warshall algorithm, visitors can take advantage of technology in their travel planning. Each algorithm has different characteristics, which allows visitors to choose according to their needs and preferences. In this digital era, the application of the algorithm not only facilitates travel planning, but also increases tourism attractiveness in Deli Serdang as a whole.

Recommendations

Based on the comparison of local beam search and Floyd-Warshall algorithm, the following recommendations can be made:

For tourists who want to travel quickly to some of the closest places, local beam search may be a better choice.
For tourists who want to optimize the most efficient route to reach many destinations, Floyd-Warshall can provide more satisfying results.
For tourists who are unsure about which algorithm to use, a combination of both local beam search and Floyd-Warshall algorithm can be used to ensure the best results.

Future Research Directions

Future research directions can include:

Developing a hybrid algorithm that combines the strengths of local beam search and Floyd-Warshall algorithm.
Applying the algorithm to other areas of tourism, such as transportation and accommodation planning.
Investigating the impact of the algorithm on tourist behavior and satisfaction.

Limitations of the Study

This study has several limitations, including:

The study only compared local beam search and Floyd-Warshall algorithm, and did not consider other algorithms.
The study only applied the algorithm to the context of tourism in Deli Serdang, and did not consider other areas of application.
The study only used a small sample size, and did not consider the impact of the algorithm on a larger scale.

Conclusion

In conclusion, the determination of the shortest route between various tourist attractions is crucial for facilitating travel, saving time, energy, and costs. Local beam search and Floyd-Warshall algorithm are two algorithms that can be used to determine the shortest route, each with its own strengths and weaknesses. By understanding the characteristics of each algorithm, tourists can choose the best option for their needs and preferences.
Frequently Asked Questions (FAQs) about Determining the Shortest Route: Local Beam Search and Floyd-Warshall Algorithm

Q: What is the main difference between Local Beam Search and Floyd-Warshall algorithm?

A: The main difference between Local Beam Search and Floyd-Warshall algorithm is the approach they use to determine the shortest route. Local Beam Search uses a hill climbing technique to find the best point around the current location, while Floyd-Warshall algorithm compares the current location with all the neighboring points to find the closest point to the final destination.

Q: Which algorithm is faster, Local Beam Search or Floyd-Warshall?

A: Local Beam Search is generally faster than Floyd-Warshall algorithm, with a trip time of 478.8 ms compared to Floyd-Warshall's execution time of 596.55 MS.

Q: Which algorithm is more suitable for complex problems with many connected points?

A: Floyd-Warshall algorithm is more suitable for complex problems with many connected points, as it evaluates all possible paths in one process.

Q: Can I use both Local Beam Search and Floyd-Warshall algorithm together?

A: Yes, you can use both Local Beam Search and Floyd-Warshall algorithm together to ensure the best results. This is known as a hybrid approach.

Q: How can I choose between Local Beam Search and Floyd-Warshall algorithm?

A: You can choose between Local Beam Search and Floyd-Warshall algorithm based on the number of tourist attractions you want to visit, the time limit of travel, and the needs of visitors. If you want to travel quickly to some of the closest places, Local Beam Search may be a better choice. If you want to optimize the most efficient route to reach many destinations, Floyd-Warshall can provide more satisfying results.

Q: Can I apply the algorithm to other areas of tourism, such as transportation and accommodation planning?

A: Yes, you can apply the algorithm to other areas of tourism, such as transportation and accommodation planning. The algorithm can be used to determine the shortest route for transportation and to optimize accommodation planning.

Q: What are the limitations of the study?

A: The study has several limitations, including the small sample size and the limited application of the algorithm to other areas of tourism.

Q: What are the future research directions?

A: Future research directions include developing a hybrid algorithm that combines the strengths of Local Beam Search and Floyd-Warshall algorithm, applying the algorithm to other areas of tourism, and investigating the impact of the algorithm on tourist behavior and satisfaction.

Q: How can I implement the algorithm in my own project?

A: You can implement the algorithm in your own project by using a programming language such as Python or Java. You can also use existing libraries and frameworks that implement the algorithm.

Q: What are the benefits of using the algorithm in tourism?

A: The benefits of using the algorithm in tourism include improved tourist experience, reduced travel time and energy expenditure, and increased economic benefits of tourism.

Q: Can I use the algorithm in other industries, such as logistics and transportation?

A: Yes, you can use the algorithm in other industries, such as logistics and transportation. The algorithm can be used to determine the shortest route for transportation and to optimize logistics planning.

Q: What are the potential applications of the algorithm in the future?

A: The potential applications of the algorithm in the future include using it in autonomous vehicles, drones, and other intelligent transportation systems. The algorithm can also be used in other areas such as supply chain management and resource allocation.