Optimization of Multitask in Real-Time Control Based on Artificial Bee Colony Algorithm

Abstract

Real-time industrial control software often has the characteristic of multitask communication within single thread, which can easily cause the thread to block. The problem can be abstracted into nonlinear constrained optimization model based on requirements of developing the industrial control software, and solved by artificial bee colony algorithm. The ABC algorithm needs less parameters, and has stronger capability of global search than other intelligent algorithms. Considering characteristics of the nonlinear constrained optimization model, three modifications are adopted to improve the capability of global search in this problem. They are a modification rate for generating a new solution, the probability of selecting a new solution by onlooker bees which is different between feasible solutions and infeasible solutions, Deb’s constrainted handling method. A comparing result shows that the modified ABC algorithm provides a better solution than GA algorithm does. By putting the solution into practice, high-speed and reliable communication can be realized between IPC, PLC and NC.