Abstract
This paper aims to simultaneously minimize logistics costs and carbon emissions. For this purpose, a mathematical model for a three-echelon supply chain network is created considering the relevant constraints such as capacity, production cost, transport cost, carbon emissions, and time window, which will be solved by the proposed quantum-particle swarm optimization algorithm. The three-echelon supply chain, consisting of suppliers, distribution centers, and retailers, is established based on the number and location of suppliers, the transport method from suppliers to distribution centers, and the quantity of products to be transported from suppliers to distribution centers and from these centers to retailers. Then, a quantum-particle swarm optimization is described as its performance is validated with different benchmark functions. The scenario analysis validates the model and evaluates its performance to balance the economic benefit and environmental effect.
Highlights
The operations in supply chain and logistics are vital tools for businesses to remain competitive in today’s important economic activities
We are motivated to study a green supply chain network design problem where an initial investment on environmental protection equipment or techniques should be determined in the design phase
The total cost of the supply chain increased with the reduction of the carbon emissions limit and the growth in the carbon emissions penalty coefficient. These laws will help enterprises optimize the design of supply chain network, making it possible to strike a balance between economic benefit and environmental effect. It is common in the logistics and supply chain that the objectives of decreasing logistic costs, carbon emissions, and increasing energy efficiency are targeted at the multi-level of the supply chain’s members
Summary
The operations in supply chain and logistics are vital tools for businesses to remain competitive in today’s important economic activities. Transportation activities are significant sources of air pollution and greenhouse gas emissions, with the former known to have harmful effects on human health and the latter being responsible for global warming. These issues have raised concerns on reducing the amount of emissions worldwide [1]. We are motivated to study a green supply chain network design problem where an initial investment on environmental protection equipment or techniques should be determined in the design phase. This investment can influence the environmental indicators in the operations phase. Decisions regarding facility location and capacity allocation have to be integrated with the decisions regarding environmental investment
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