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Particle Swarm Optimization Algorithm of Pellet Burden Cost Optimization Based on Penalty Function | IEEE Conference Publication | IEEE Xplore

Particle Swarm Optimization Algorithm of Pellet Burden Cost Optimization Based on Penalty Function


Abstract:

Taking the lowest cost as the objective, considering the influence of the weight gain of iron oxide oxidation process, the burning loss of raw materials and the amount of...Show More

Abstract:

Taking the lowest cost as the objective, considering the influence of the weight gain of iron oxide oxidation process, the burning loss of raw materials and the amount of desulfurization on the chemical composition and cost of pellet products, this paper constructs an optimization model of pellet proportioning, and gives the particle swarm optimization algorithm based on penalty function. This model can not only meet the chemical composition requirements of finished ore, but also reduce the cost effectively, and greatly reduce the time cost of calculation. Compared with the existing research results, it has higher calculation efficiency on the basis of ensuring the accuracy of calculation results.
Date of Conference: 04-06 May 2022
Date Added to IEEE Xplore: 20 May 2022
ISBN Information:
Conference Location: Hangzhou, China

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