Production management and control based on ant colony optimization and neural network

Abstract

The neural network (NN) has an advantage in handling the massive real-time monitoring data on discrete manufacturing. Therefore, this paper proposes a production management and control method for discrete manufacturing job-shops based on ant colony optimization (ACO). Firstly, the production management and control problem for discrete manufacturing job-shops was described through the functional analysis on the management and control system, followed by establishing the corresponding mathematical model. After that, the ACO was improved to solve the static multi-objective production management and control problem. Then, the authors set up an NN-based production management and control model for dynamic discrete manufacturing job-shop, and detailed the way to select and transform the judgement result on production state and to set up the training set. Finally, the effectiveness of our algorithm was verified through experiments.