The Sparrow Search Algorithm (SSA) is a meta-heuristic optimization algorithm based on the anti-predation and foraging behavior of sparrows.
The foraging behavior of sparrows can be divided into two main types: producers and scavengers. Producers actively search for food, while scavengers compete for food from producers.
In the Sparrow Search Algorithm (SSA), each sparrow pays close attention to the behavior of its neighbors. By employing different foraging strategies, individuals are able to efficiently use retained energy to pursue more food. Additionally, birds are more vulnerable to predators in their search space, so they need to find safer locations. Birds at the center of a colony can minimize their own range of danger by staying close to their neighbors. When a bird spots a predator, it emits an alarm call so that the entire group can quickly escape from the source of danger.
Based on the above description of Sparrow, a mathematical model can be established to construct the SSA algorithm.
In the algorithm simulation experiment, a virtual sparrow is used to track the food source, and its position vector is expressed as:
where the sparrow’s The quantity is represented by N, and the dimension to be optimized is represented by D. Then, the following vector can represent the fitness values of all sparrows:
The value of each row is F(X)
j∈{1,2,…,D}j∈{1,2,…,D}R2∈[0,1]R2∈[0,1]ST∈[0.5,1.0]ST∈[0.5,1.0]α∈(0,1]α∈(0,1]1×D1×DR2<STR2<STR2≥STAs mentioned above, scavengers will continue to track producers until those producers find a good food source so that they can leave their current location to search for it Target food sources. If they win, the scavengers will receive food from the producers; otherwise, they will continue their vigilance mission. Pickers update their positions according to Eq.
xp,jxp,jxworst,jxworst,j1×D1×D−1−1A+=AT(AAT)−1A+=AT(AAT)−11×D1×Di>N/
##Standard Sparrow Search Algorithm (SSA) Structure
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