Abstract

Traditional research on production scheduling in aluminum industry, aimed to certain production process, simply pursued the output as the highest aim, scheduled based on experience, so that the result of scheduling cannot reach the global optimization, and cannot realize production scheduling and resource allocation with the aim of optimal energy consumption, resulting in the waste of energy. Taken the minimal sum of energy consumption in production, transport and stock as objective function and integrated with enterprise’s experiences in production, the article establishes a model of virtual enterprise’s task scheduling in aluminum industry and a hybrid distributed particle swarm optimization (PSO) algorithm is proposed to solve the problem. Finally, simulation experiment is carried out using industrial data and the result shows the optimized scheduling method has obvious optimal effect on reducing scheduling time, optimizing allocation of resources and so on, and thus the energy saving and consumption reducing purpose are obtained. 

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