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首页> 外文期刊>Journal of the air & waste management association >A multiobjective optimization model and an orthogonal design-based hybrid heuristic algorithm for regional urban mining management problems
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A multiobjective optimization model and an orthogonal design-based hybrid heuristic algorithm for regional urban mining management problems

机译:区域城市采矿管理问题的多目标优化模型和基于正交设计的混合启发式算法

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摘要

In this paper, a multiobjective mixed-integer piecewise nonlinear programming model (MOMIPNLP) is built to formulate the management problem of urban mining system, where the decision variables are associated with buy-back pricing, choices of sites, transportation planning, and adjustment of production capacity. Different from the existing approaches, the social negative effect, generated from structural optimization of the recycling system, is minimized in our model, as well as the total recycling profit and utility from environmental improvement are jointly maximized. For solving the problem, the MOMIPNLP model is first transformed into an ordinary mixed-integer nonlinear programming model by variable substitution such that the piecewise feature of the model is removed. Then, based on technique of orthogonal design, a hybrid heuristic algorithm is developed to find an approximate Pareto-optimal solution, where genetic algorithm is used to optimize the structure of search neighborhood, and both local branching algorithm and relaxation-induced neighborhood search algorithm are employed to cut the searching branches and reduce the number of variables in each branch. Numerical experiments indicate that this algorithm spends less CPU (central processing unit) time in solving large-scale regional urban mining management problems, especially in comparison with the similar ones available in literature. By case study and sensitivity analysis, a number of practical managerial implications are revealed from the model. Implications: Since the metal stocks in society are reliable overground mineral sources, urban mining has been paid great attention as emerging strategic resources in an era of resource shortage. By mathematical modeling and development of efficient algorithms, this paper provides decision makers with useful suggestions on the optimal design of recycling system in urban mining. For example, this paper can answer how to encourage enterprises to join the recycling activities by government's support and subsidies, whether the existing recycling system can meet the developmental requirements or not, and what is a reasonable adjustment of production capacity.
机译:本文建立了一个多目标混合整数分段非线性规划模型(MOMIPNLP)来表达城市采矿系统的管理问题,其中决策变量与回购价格,选址,运输计划以及对项目的调整有关。生产能力。与现有方法不同,在我们的模型中,将回收系统的结构优化所产生的社会负面影响最小化,同时将环境改善带来的总回收利润和效用最大化。为了解决该问题,首先通过变量替换将MOMIPNLP模型转换为普通的混合整数非线性规划模型,从而消除了模型的分段特征。然后,在正交设计技术的基础上,发展了一种混合启发式算法来寻找近似的帕累托最优解,其中采用遗传算法对搜索邻域的结构进行优化,同时采用局部分支算法和松弛诱导邻域搜索算法。用于削减搜索分支并减少每个分支中的变量数量。数值实验表明,该算法在解决大规模区域性城市采矿管理问题上花费的CPU(中央处理器)时间更少,特别是与文献中类似的算法相比。通过案例研究和敏感性分析,该模型揭示了许多实际的管理意义。启示:由于社会上的金属储备是可靠的地上矿产资源,在资源短缺的时代,城市采矿作为新兴的战略资源受到了高度重视。通过数学建模和高效算法的开发,本文为决策者提供了有关城市采矿中回收系统优化设计的有用建议。例如,本文可以回答如何在政府的支持和补贴下鼓励企业参加回收活动,现有的回收系统是否能够满足发展要求,以及合理地调整生产能力。

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    Hao Wu; Zhong Wan;

  • 作者单位

    School of Mathematics and Statistics, Central South University, Changsha, People's Republic of China,School of Finance and Statistics, Hunan University, Changsha, People's Republic of China;

    School of Mathematics and Statistics, Central South University, Changsha, People's Republic of China;

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