Feature selection is the process of identifying relevant features and removing irrelevant and repetitive features with the aim of observing a subset of features that describe the problem well and with minimal loss of efficiency. One of the feature selection approaches is using optimization algorithms. This work provides a summary of some meta-heuristic feature selection methods proposed from 2018 to 2021 that were designed and implemented on a wide range of different data. The results of the study showed that some meta-heuristic algorithms alone cannot perfectly solve the feature selection problem on all types of datasets with an acceptable speed. In other words, depending on dataset, a special meta-heuristic algorithm should be used. تفاصيل المقالة

Here we discuss the problem of distribution of Real_time processes on multiprocessor with on-time maximum job accomplished. Scientists have been searching for producing optimized scheduling.this is an example of NP problems.this is not practical to approach this kind of problems with heuristic approach thus we must use meta-heuristic algorithms.These algorithms present many sets of answers in order to make options for scheduler, to choose the best process assignment to processor. Two examples are Branch and Bound, and Task Graph Algorithms. By studying the ant colony,Genetics and PSO Algorithms, we will design and consider several methods for our purpose and use them to produce Job assignment Scheduler, on processors. Each of these algorithms will provide us with a specific designing method and help us to make a scheduler engine of real_time processes assignment on processors. We will compare each program to the first heuristic one, to assess the manufactured programs. In comparisons which are based on lost processes, Colony approach has 11.94 % ,PSO approach 11.19 %, and Genetic approach has 7.52 % less process lost in compare to heuristic approach. It worth mention that 20 files each of which containing 50 Real_time process have been used In these experiments. تفاصيل المقالة