0. Foreword
This blog post simulates and verifies the effect of the improved sparrow optimization algorithm (IAMSSA) that combines elite strategy tent perturbation and Cauchy mutation on function extreme value optimization.
1. Analysis of improvement points
① Cat chaotic map initialization population: Cat map is a two-dimensional reversible chaotic map, which has better ergodic uniformity and faster iteration speed, and the chaotic sequence generated between [0, 1] is evenly distributed.
②Elite Reverse Strategy: Taking advantage of the advantage that elite individuals have more useful information than ordinary individuals, construct a reverse population through the elite individuals in the current population to join the current population, increase the diversity of the population, and select from the expanded new population The optimal specific individuals form a new generation of individuals, which enters into iterative update.
③Scale factor improvement: r dynamic update, dynamically adjust the number of discoverers and the number of sparrows aware of danger
PDNumber = round(pop*r); %Number of discoverers
SDNumber = round(r*pop);%Number of sparrows aware of danger
④Improved explorer position update formula
⑤ tent disturbance and Cauchy mutation: prevent falling into local optimum
2. Effect display
