Learning from ants

Learning from ants: Ant colony optimization algorithms are versatile and useful for several real-world applications. These applications usually center on complex optimization problems. Here are three uses for the algorithm.

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Route optimization

In a logistics example, perhaps the distance between destinations, traffic conditions, types of packages being delivered, and times of day are important constraints to optimize the operations of the business. ACOs can help with that.

Job scheduling

Job scheduling is required in almost any industry. Nurse shifts are important to ensure that good health care can be provided while keeping nurses healthy. Computational jobs on servers must be scheduled in an optimal manner to maximize the use of the hardware.11

Image processing

Although there are better ways, ACOs can be used for edge detection in image processing. An image is composed of several adjacent pixels, and the ants can move from pixel to pixel, leaving behind pheromone trails that would trace an object.

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