Shipping Logistics Network Optimization with Stochastic Demands for Construction Waste Recycling: A Case Study in Shanghai, China DOI Open Access
Ping Wu, Yue Song, Xiangdong Wang

et al.

Sustainability, Journal Year: 2025, Volume and Issue: 17(3), P. 1037 - 1037

Published: Jan. 27, 2025

In this paper, we introduce a shipping logistics network optimization method for construction waste recycling. our case, is transported by relay mode integrating land transportation, and transportation. Under the influence of urban economic life, quantity (demand) uncertain stochastic. Considering randomness generation, two-stage stochastic integer programming model design recycling proposed, an accurate algorithm based on Benders decomposition presented. Based actual case in Shanghai, numerical experiments are carried out to evaluate efficacy proposed algorithm. study demonstrate that can help reduce transportation costs waste. Sensitivity analysis highlights factors like penalty untransported capacity constraints play crucial role decisions. The findings provide valuable theoretical support developing more efficient sustainable networks

Language: Английский

Shipping Logistics Network Optimization with Stochastic Demands for Construction Waste Recycling: A Case Study in Shanghai, China DOI Open Access
Ping Wu, Yue Song, Xiangdong Wang

et al.

Sustainability, Journal Year: 2025, Volume and Issue: 17(3), P. 1037 - 1037

Published: Jan. 27, 2025

In this paper, we introduce a shipping logistics network optimization method for construction waste recycling. our case, is transported by relay mode integrating land transportation, and transportation. Under the influence of urban economic life, quantity (demand) uncertain stochastic. Considering randomness generation, two-stage stochastic integer programming model design recycling proposed, an accurate algorithm based on Benders decomposition presented. Based actual case in Shanghai, numerical experiments are carried out to evaluate efficacy proposed algorithm. study demonstrate that can help reduce transportation costs waste. Sensitivity analysis highlights factors like penalty untransported capacity constraints play crucial role decisions. The findings provide valuable theoretical support developing more efficient sustainable networks

Language: Английский

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