Expected energy analysis for industrial process planning problem with fuzzy time parameters

Industrial process planning is to make an optimal decision in terms of resource allocation. The planning objective can be to minimize the time required to complete a task, maximize customer satisfaction by completing orders in a timely fashion and minimize the cost required to complete a task. Based on time and energy consumption in an industrial process planning problem, a novel energy analysis method is proposed to solve it. According to different constraints and credibility theory, typical expected value models of energy for it are presented. In addition, a hybrid intelligent optimization algorithm integrating fuzzy simulation, neural network and genetic algorithm is provided for solving the proposed expected value models. Some numerical examples are also given to illustrate the proposed concepts and the effectiveness of the used algorithm.

► We propose a novel energy analysis method integrating multiple variables. ► We establish three typical expected value models for industrial planning problem. ► An algorithm integrating fuzzy simulation, NN and GA is used to solve proposed models.