Related Experiment Video
Updated: Oct 20, 2025
11:53
Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
Published on: December 9, 2012
13.1K
An improved ant colony optimization algorithm based on context for tourism route planning
Shengbin Liang1, Tongtong Jiao1, Wencai Du2
1School of Software, Henan University, Kaifeng, Henan, China.
Plos One
|September 16, 2021
Summary
This study introduces an improved ant colony optimization algorithm for tourism route planning. The enhanced algorithm prioritizes tourist experience and optimizes routes, reducing travel distance and improving efficiency.
Area of Science:
- Computer Science
- Artificial Intelligence
- Operations Research
Background:
- Traditional tourism route planning often prioritizes shortest distance over tourist experience.
- Scenic spot context, including weather and comfort, significantly influences destination choice.
- Existing algorithms may fall into local optima, failing to find globally optimal routes.
Purpose of the Study:
- To develop an improved ant colony optimization algorithm for tourism route planning.
- To integrate contextual information of scenic spots into the route optimization process.
- To enhance the tourist experience by optimizing routes beyond mere distance.
Main Methods:
- An improved ant colony optimization algorithm was proposed.
- Pheromone update strategy was combined with contextual information (weather, comfort).
- Sub-path support degree was introduced to avoid local optimization.
Main Results:
- The optimized tourism routes significantly improved the tourist experience.
- Route distance was shortened by 20.5% compared to the basic algorithm.
- Convergence speed increased by 21.2% compared to the basic algorithm.
Conclusions:
- The improved ant colony optimization algorithm is effective for tourism route planning.
- Integrating contextual information enhances route suitability for tourists.
- The algorithm successfully balances route efficiency with improved tourist satisfaction.
Related Concept Videos
00:48Optimal Foraging
12.6K
How animals obtain and eat their food is called foraging behavior. Foraging can include searching for plants and hunting for prey and depends on the species and environment.
12.6K
01:21Heuristics
182
Heuristics are problem-solving strategies that use mental shortcuts to simplify decision-making. Unlike algorithms, which must be followed precisely to achieve a correct result, heuristics offer a general problem-solving framework. They save time and energy but can sometimes lead to less rational decisions.
People often rely on heuristics when faced with an overload of information, limited time, low importance of the decision, limited information, or when a heuristic readily comes to mind. For...
People often rely on heuristics when faced with an overload of information, limited time, low importance of the decision, limited information, or when a heuristic readily comes to mind. For...
182
02:12Short-distance Transport of Resources
16.7K
Short-distance transport refers to transport that occurs over a distance of just 2-3 cells, crossing the plasma membrane in the process. Small uncharged molecules, such as oxygen, carbon dioxide, and water, can diffuse across the plasma membrane on their own. In contrast, ions and larger molecules require the assistance of transport proteins due to their charge or size. Transport across membranes also occurs within individual cells, playing a variety of essential roles for the plant as a whole.
16.7K
01:20Cluster Sampling Method
13.2K
Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
13.2K
01:17Design Example: Alignment of a Road Line Using GIS
136
The alignment of a road line using Geographic Information Systems (GIS) is a critical process in civil engineering, combining advanced technology with practical decision-making. This methodology begins with the collection of geospatial data, including information on land cover, geomorphology, drainage patterns, slope, and contour details. Such data is typically acquired through satellite imagery and GIS tools, offering a comprehensive understanding of the terrain.Once the data is gathered, it...
136
01:29Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving
130
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
130