| 考虑碳排放成本的长江铁矿石运输研究 |
| 投稿时间：2021-03-29 修订日期：2021-04-20 点此下载全文 |
| 引用本文：赵晓,胡鸿韬.考虑碳排放成本的长江铁矿石运输研究[J].上海海事大学学报,2021,42(3):29-35. |
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| 基金项目:国家自然科学基金（71771143） |
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| 中文摘要:为降低钢铁企业采购和运输铁矿石的综合成本，考虑船型、航速和碳排放等因素，建立长江铁矿石运输的混合整数非线性规划模型。将模型中的非线性项转化为线性项，运用CPLEX求解器求解。针对CPLEX求解中大型规模算例的局限性，引入标准粒子群优化（particle swarm optimization, PSO）算法提高求解精度。针对标准PSO算法容易陷入局部最优的问题，提出一种基于自适应策略的改进PSO算法，动态调整惯性权重，提高算法的收敛性和全局寻优能力。通过数值实验发现，改进后的算法在全局寻优能力和收敛能力上有一定的提高。 |
| 中文关键词:多层级运输网络 碳排放 混合整数非线性规划 粒子群优化(PSO)算法 |
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| Research on iron ore transportation in the Yangtze River considering carbon emission cost |
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| Abstract:In order to reduce the overall cost of steel companies purchasing and transporting iron ore, taking into account factors such as ship type, navigation speed and carbon emission, a mixed integer nonlinear programming model of iron ore transportation in the Yangtze River is established. In the model, the nonlinear terms are converted into the linear terms, and the CPLEX solver is used to solve the model. Aiming at the limitation of CPLEX in solving medium and large scale cases, the standard particle swarm optimization (PSO) algorithm is used to improve the accuracy of solutions. For the problem that the standard PSO algorithm is easy to fall into the local optimum, an improved PSO algorithm based on adaptive strategy is proposed, which can dynamically adjust the inertia weight to improve the algorithm’s convergence and global optimization ability. Through numerical experiments, it is found that the improved algorithm has a certain improvement in the global optimization ability and convergence ability. |
| keywords:multi level transportation network carbon emission mixed integer nonlinear programming particle swarm optimization (PSO) algorithm |
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