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Discrete logistics network design model under interval hierarchical OD demand based on interval genetic algorithm

Journal of Central South University 2013年第9期20卷 2625-2634页

作者：李利华符卓周和平胡正东 School of Traffic and Transport Engineering Changsha University of Science and Technology School of Traffic and Transport Engineering Central South University School of Politics and Public Administration University of South China

Aimed at the uncertain characteristics of discrete logistics network design,an interval hierarchical triangular uncertain OD demand model based on interval demand and network flow is *** consideration of the system profit,the uncertain demand of logistics network is measured by interval variables and interval parameters,and an interval planning model of discrete logistics network is *** risk coefficient and maximum constrained deviation are defined to realize the certain transformation of the *** integrating interval algorithm and genetic algorithm,an interval hierarchical optimal genetic algorithm is proposed to solve the *** is shown by a tested example that in the same scenario condition an interval solution[3275.3,3 603.7]can be obtained by the model and algorithm which is obviously better than the single precise optimal solution by stochastic or fuzzy algorithm,so it can be reflected that the model and algorithm have more stronger operability and the solution result has superiority to scenario decision.

关键词： uncertainty interval planning hierarchical OD logistics network design genetic algorithm

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An Artificial Neural network-Based Method for Railway logistics network design

An Artificial Neural Network-Based Method for Railway Logist...

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2012 3rd International Conference on Information Technology for Manufacturing Systems(ITMS 2012)

作者： Wang Danzhu Lang Maoxiang Beijing Jiaotong University

logistics network design problem has an important position in the railway logistics development, it has aroused great concern both in railway transportation and logistics research fields. This paper proposes a method for railway logistics network design problem based on artificial neural network model. In the logistics network design method, various influencing factors of railway logistics network have been considered. An evaluation index system of a railway transportation enterprise is set up. Self-Organizing Map neural network algorithm has been used for the creation of logistics network nodes initial set. And the layers division of the logistics network has been determined with the help of BP neural network model. Subsequently an empirical study of a railway logistics enterprise is given to certificate the feasibility and accuracy of this railway logistics network design method.

关键词： railway logistics network design Self-Organizing Map neural network BP neural network

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Two-stage stochastic programming with robust constraints for the logistics network post-disruption response strategy optimization

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Frontiers of Engineering Management 2023年第1期10卷 67-81页

作者： Xiaotian ZHUANG Yuli ZHANG Lin HAN Jing JIANG Linyuan HU Shengnan WU JD logistics Beijing 100176China School of Management and Economics Beijing Institute of TechnologyBeijing 100081China Yangtze Delta Region Academy of Beijing Institute of Technology Jiaxing 314019China

logistics networks (LNs) are essential for the transportation and distribution of goods or services from suppliers to consumers. However, LNs with complex structures are more vulnerable to disruptions due to natural disasters and accidents. To address the LN post-disruption response strategy optimization problem, this study proposes a novel two-stage stochastic programming model with robust delivery time constraints. The proposed model jointly optimizes the new-line-opening and rerouting decisions in the face of uncertain transport demands and transportation times. To enhance the robustness of the response strategy obtained, the conditional value at risk (CVaR) criterion is utilized to reduce the operational risk, and robust constraints based on the scenario-based uncertainty sets are proposed to guarantee the delivery time requirement. An equivalent tractable mixed-integer linear programming reformulation is further derived by linearizing the CVaR objective function and dualizing the infinite number of robust constraints into finite ones. A case study based on the practical operations of the JD LN is conducted to validate the practical significance of the proposed model. A comparison with the rerouting strategy and two benchmark models demonstrates the superiority of the proposed model in terms of operational cost, delivery time, and loading rate.

关键词： logistics network design post-disruption response strategy two-stage stochastic programming conditional value at risk robust constraint

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