scholarly journals Multi-Objective Optimization of Green Supply Chain Network Designs for Transportation Mode Selection

2017 ◽  
Vol 0 (0) ◽  
pp. 0-0 ◽  
Author(s):  
Dah-Chuan Gong ◽  
Ping-Shun Chen ◽  
Tzu-Yang Lu
Keyword(s):  
Supply Chain ◽  
Mode Selection ◽  
Green Supply Chain ◽  
Supply Chain Network ◽  
Multi Objective Optimization ◽  
Transportation Mode ◽  
Multi Objective ◽  
Transportation Mode Selection

Multi-Objective Optimization for Green Dual-Channel Supply Chain Network Design Considering Transportation Mode Selection

2018 ◽  
Vol 11 (3) ◽  
pp. 1-21 ◽  
Author(s):  
Hong Zhang ◽  
Kuan Yang
Keyword(s):  
Supply Chain ◽  
Environmental Performance ◽  
Mode Selection ◽  
Supply Chain Network ◽  
Transportation Mode ◽  
Trade Off ◽  
Multi Objective ◽  
Dual Channel ◽  
Transportation Mode Selection ◽  
Dual Channel Supply Chain

A well-designed supply chain network should not only meet the efficient cost but also realize the sustainable effect on environment. The purpose of this article is to develop a multi-objective model to capture the trade-off between total cost and environmental performance in the green dual-channel supply chain network. Moreover, the transportation mode has been considered as a decision variable. With regard to the complexity of such network, a new swarm intelligence algorithm known as a multi-objective particle swarm optimization (MOPSO) algorithm has been employed to tackle this problem. The effectiveness of the present model and approach is evaluated by a numerical experiment, and the results show that the added environmental performance is actually proportional with the increased cost. Additionally, the comparison between different mode decisions shows that a better trade-off between two objectives will be obtained when considering the transportation mode selection.

Multi-Objective Optimization for Green Dual-Channel Supply Chain Network Design Considering Transportation Mode Selection

2020 ◽  
pp. 382-404
Author(s):  
Hong Zhang ◽  
Kuan Yang
Keyword(s):  
Supply Chain ◽  
Environmental Performance ◽  
Mode Selection ◽  
Supply Chain Network ◽  
Transportation Mode ◽  
Trade Off ◽  
Multi Objective ◽  
Dual Channel ◽  
Transportation Mode Selection ◽  
Dual Channel Supply Chain

A well-designed supply chain network should not only meet the efficient cost but also realize the sustainable effect on environment. The purpose of this article is to develop a multi-objective model to capture the trade-off between total cost and environmental performance in the green dual-channel supply chain network. Moreover, the transportation mode has been considered as a decision variable. With regard to the complexity of such network, a new swarm intelligence algorithm known as a multi-objective particle swarm optimization (MOPSO) algorithm has been employed to tackle this problem. The effectiveness of the present model and approach is evaluated by a numerical experiment, and the results show that the added environmental performance is actually proportional with the increased cost. Additionally, the comparison between different mode decisions shows that a better trade-off between two objectives will be obtained when considering the transportation mode selection.

A multi-objective optimization model for sustainable supply chain network with using genetic algorithm

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Reza Ehtesham Rasi ◽  
Mehdi Sohanian
Keyword(s):  
Supply Chain ◽  
Performance Indicators ◽  
Supplier Selection ◽  
Supply Chain Network ◽  
Sustainable Supply Chain ◽  
Multi Objective Optimization ◽  
Content Type ◽  
Sustainability Performance ◽  
Multi Objective ◽  
Sustainable Supplier Selection

Purpose The purpose of this paper is to design and optimize economic and environmental dimensions in a sustainable supply chain (SSC) network. This paper developed a mixed-integer linear programing (MILP) model to incorporate economical and environmental data for multi-objective optimization of the SSC network. Design/methodology/approach The overall objective of the present study is to use high-quality raw materials, at the same time the lowest amount of pollution emission and the highest profitability is achieved. The model in the problem is solved using two algorithms, namely, multi-objective genetic and multi-objective particle swarm. In this research, to integrate sustainable supplier selection and optimization of sustainability performance indicators in supply chain network design considering minimization of cost and time and maximization of sustainability indexes of the system. Findings The differences found between the genetic algorithms (GAs) and the MILP approaches can be explained by handling the constraints and their various logics. The solutions are contrasted with the original crisp model based on either MILP or GA, offering more robustness to the proposed approach. Practical implications The model is applied to Mega Motor company to optimize the sustainability performance of the supply chain i.e. economic (cost), social (time) and environmental (pollution of raw material). The research method has two approaches, namely, applied and mathematical modeling. Originality/value There is limited research designing and optimizing the SSC network. This study is among the first to integrate sustainable supplier selection and optimization of sustainability performance indicators in supply chain network design considering minimization of cost and time and maximization of sustainability indexes of the system.

A MULTI OBJECTIVE MODEL FOR OPTIMIZATION OF A GREEN SUPPLY CHAIN NETWORK

2010 ◽  
Author(s):  
Turan Paksoy ◽  
Eren Özceylan ◽  
Gerhard-Wilhelm Weber ◽  
Nader Barsoum ◽  
G. W. Weber ◽  
...  
Keyword(s):  
Supply Chain ◽  
Green Supply Chain ◽  
Supply Chain Network ◽  
Multi Objective ◽  
Objective Model
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