Low-carbon Marine Logistics Network Design under Double Uncertainty of Market Demand and Carbon Trading Price

2019 ◽  
Vol 94 (sp1) ◽  
pp. 30
Author(s):  
Wei Wang ◽  
Ying Ren ◽  
Wenliang Bian ◽  
Xinyue Jia
Keyword(s):  
Network Design ◽  
Carbon Trading ◽  
Market Demand ◽  
Low Carbon ◽  
Logistics Network

A genetic algorithm for fuzzy random and low-carbon integrated forward/reverse logistics network design

2019 ◽  
Vol 32 (7) ◽  
pp. 2005-2025 ◽  
Author(s):  
Yangjun Ren ◽  
Chuanxu Wang ◽  
Botang Li ◽  
Chao Yu ◽  
Suyong Zhang
Keyword(s):  
Genetic Algorithm ◽  
Network Design ◽  
Reverse Logistics ◽  
Low Carbon ◽  
Logistics Network ◽  
Reverse Logistics Network ◽  
Fuzzy Random

Regional low-carbon timber logistics network design and management using multi-objective optimization

2017 ◽  
Vol 22 (6) ◽  
pp. 354-362 ◽  
Author(s):  
Cheng Chen ◽  
Xisheng Hu ◽  
Jianbang Gan ◽  
Rongzu Qiu
Keyword(s):  
Network Design ◽  
Low Carbon ◽  
Multi Objective Optimization ◽  
Logistics Network ◽  
Multi Objective

Research on Remanufacturing Closed-Loop Logistics Network Design under Low-Carbon Restriction

2012 ◽  
Vol 159 ◽  
pp. 224-234
Author(s):  
Ya Can Wang ◽  
Tao Lu ◽  
Chun Hua Gao ◽  
Chun Hui Zhang ◽  
Chi Chen
Keyword(s):  
Network Design ◽  
Co2 Emission ◽  
Closed Loop ◽  
Programming Model ◽  
Pareto Frontier ◽  
Mixed Integer ◽  
Low Carbon ◽  
Waste Generation ◽  
Low Carbon Economy ◽  
Logistics Network

In this paper we study how to trade off the economic and ecological effects in the remanufacturing closed-loop logistics network design in the context of low-carbon economy. We establish a multi-objective mixed integer linear programming model to find the optimal facility locations and materials flow allocation. In the objective function, we set three minimum targets: economic cost, CO2 emission and waste generation. Through an iterative algorithm, we get the Pareto Frontier of our problem. In the numeric study, we find that in order to achieve a Pareto improvement over an original system, three of the critical rates (i.e. return rate, recovery rate, and cost substitute rate) should be increased. Also, to meet the need of low-carbon dioxide, we plot an iso-CO2 emission curve in which decision makers have a series of optimal choices with the same CO2 emission but different cost and waste generation. Each choice may have different network design but all of these are Pareto optimal solutions, which provide a comprehensive evaluation of both economics and ecology for the decision making.

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