Reliable design of urban surface-underground integrated logistics system network with stochastic demand and social-environmental concern

Dong, Jianjun; Yang, Kai; Hwang, Bon‐Gang; Ren, Rui; Chen, Zhilong

doi:10.1016/j.cie.2023.109331

Cited by 8 publications

(2 citation statements)

References 51 publications

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“…Recently, a methodology proposed by Hu et al [21] revolves around optimizing crucial decisions and considering uncertainties in crafting an integrated urban surfaceunderground logistics network. The findings underscore its effectiveness in achieving a nuanced equilibrium between conservatism and optimality in the intricate domain of network design.…”

Section: Underground Logistics Networkmentioning

confidence: 99%

A Hybrid Heuristic Algorithm for Maximizing the Resilience of Underground Logistics Network Planning

Xue,

Fang,

Peng

et al. 2023

Applied Sciences

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In recent times, there has been a sharp increase in the congestion of ground transportation, the scarcity of land resources, and various disasters. Hence, there is an urgent need to find an effective and sustainable approach to transportation. The construction of an underground logistics network, where transportation activities occur beneath the surface of the ground, is anticipated to emerge as a future trend. This study aims to formulate a resilient-maximizing plan for the underground logistics network, ensuring optimal meeting of transportation demands in the aftermath of ground disasters. Accordingly, a two-stage linear programming model is established to determine the layout plan for the most resilient underground logistics network. The first phase of the model is designed to generate viable layouts for the underground logistics network, while the second phase is dedicated to evaluating the resilience of the proposed layout plan. During the evaluation of network resilience, Monte Carlo simulations are used to simulate disaster scenarios. Given the inherent complexity of the model, the traditional solver cannot efficiently solve the problem. Thus, a new hybrid heuristic algorithm is designed to obtain solutions that maximize network resilience. The results show the effectiveness of the designed algorithm and the significant improvement in network resilience achieved by numerical experiments. Moreover, sensitivity analyses are conducted to reveal the relationships between resilience and budget, as well as resilience and the capacity of underground pipelines. It has a significant impact on sustainability when making decisions regarding network planning.

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Section: Underground Logistics Networkmentioning

confidence: 99%

A Hybrid Heuristic Algorithm for Maximizing the Resilience of Underground Logistics Network Planning

Xue,

Fang,

Peng

et al. 2023

Applied Sciences

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“…Equation ( 19) is formulated to monetize the land conservation benefit. Equation (20) demonstrates the environmental benefits brought by the UWCS, including reduced pollution benefits and non-renewable energy savings benefits [14,48]. Pollution benefits are calculated by multiplying the emission factors for various pollutants generated by truck transport of MSW and the unit treatment cost of these pollutants by the ground transportation miles of the UWCS network instead of trucks.…”

Section: Quantifying Uwcs Benefitsmentioning

confidence: 99%

Underground Logistics Network Design for Large-Scale Municipal Solid Waste Collection: A Case Study of Nanjing, China

Liu,

Chen,

et al. 2023

Sustainability

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The challenges arising from the management of municipal solid waste (MSW) have a profound impact on the sustainable development of urban areas. As a sustainable solution, the transportation of MSW underground offers the potential to alleviate traffic congestion and reduce environmental pollution. In this study, we propose the implementation of a large-scale underground waste collection system (UWCS). To begin, a comprehensive operational process for the UWCS is designed based on an intelligent technology system, including facility operation, processing workflow, and technical parameters. Additionally, network planning methods for the UWCS are presented. A mixed-integer linear programming model is formulated with the objective of minimizing total cost. This model determines the optimal location and allocation of nodes within the network, as well as the pipeline layout and flow direction. Given the computational complexity, a hybrid optimization method, namely the genetic greedy algorithms and genetic variable neighborhood search algorithms (GGA-GVNS), is devised to obtain high-quality solutions for the model. Finally, to validate the efficacy of the proposed method, a simulation is conducted in the central city of Nanjing, China. The results demonstrate that the implementation of the UWCS network in Nanjing’s city center can yield an annual benefit of USD 5.99 million. Moreover, a sensitivity analysis reveals further MSW management-related insights and long-term planning strategies.

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Optimizing the Laboratory Supply Chain with Clarke and Wright Fuzzy Algorithm

del Villar Labastida,

Sánchez

2024

Lecture Notes in Networks and Systems

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Reliable design of urban surface-underground integrated logistics system network with stochastic demand and social-environmental concern

Cited by 8 publications

References 51 publications

A Hybrid Heuristic Algorithm for Maximizing the Resilience of Underground Logistics Network Planning

A Hybrid Heuristic Algorithm for Maximizing the Resilience of Underground Logistics Network Planning

Underground Logistics Network Design for Large-Scale Municipal Solid Waste Collection: A Case Study of Nanjing, China

Optimizing the Laboratory Supply Chain with Clarke and Wright Fuzzy Algorithm

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