scholarly journals A Multiperiod Supply Chain Network Design Considering Carbon Emissions

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Yang Peng ◽  
Jose Humberto Ablanedo-Rosas ◽  
Peihua Fu

This paper introduces a mixed integer linear programming formulation for modeling and solving a multiperiod one-stage supply chain distribution network design problem. The model is aimed to minimize two objectives, the total supply chain cost and the greenhouse gas emissions generated mainly by transportation and warehousing operations. The demand forecast is known for the planning horizon and shortage of demand is allowed at a penalty cost. This scenario must satisfy a minimum service level. Two carbon emission regulatory policies are investigated, the tax or carbon credit and the carbon emission cap. Computational experiments are performed to analyze the trade-offs between the total cost of the supply chain, the carbon emission quantity, and both carbon emission regulatory policies. Results demonstrate that for a certain range the carbon credit price incentivizes the reduction of carbon emissions to the environment. On the other hand, modifying the carbon emission cap inside a certain range could lead to significant reductions of carbon emission while not significantly compromising the total cost of the supply chain.

Author(s):  
Peng Li ◽  
Di Wu

The rapid development of e-commerce technologies has encouraged collection centers to adopt online recycling channels in addition to their existing traditional (offline) recycling channels, such the idea of coexisting traditional and online recycling channels evolved a new concept of a dual-channel reverse supply chain (DRSC). The adoption of DRSC will make the system lose stability and fall into the trap of complexity. Further the consumer-related factors, such as consumer preference, service level, have also severely affected the system efficiency of DRSC. Therefore, it is necessary to help DRSCs to design their networks for maintaining competitiveness and profitability. This paper focuses on the issues of quantitative modelling for the network design of a general multi-echelon, dual-objective DRSC system. By incorporating consumer preference for the online recycling channel into the system, we investigate a mixed integer linear programming (MILP) model to design the DRSC network with uncertainty and the model is solved using the ε-constraint method to derive optimal Pareto solutions. Numerical results show that there exist positive correlations between consumer preference and total collective quantity, online recycling price and the system profits. The proposed model and solution method could assist recyclers in pricing and service decisions to achieve a balance solution for economic and environmental sustainability.


2017 ◽  
Vol 117 (10) ◽  
pp. 2468-2484 ◽  
Author(s):  
Xu Chen ◽  
Xiaojun Wang

Purpose In the era of climate change, industrial organizations are under increasing pressure from consumers and regulators to reduce greenhouse gas emissions. The purpose of this paper is to examine the effectiveness of product mix as a strategy to deliver the low carbon supply chain under the cap-and-trade policy. Design/methodology/approach The authors incorporate the cap-and-trade policy into the green product mix decision models by using game-theoretic approach and compare these decisions in a decentralized model and a centralized model, respectively. The research explores potential behavioral changes under the cap-and-trade in the context of a two-echelon supply chain. Findings The analysis results show that the channel structure has significant impact on both economic and environmental performances. An integrated supply chain generates more profits. In contrast, a decentralized supply chain has lower carbon emissions. The cap-and-trade policy makes a different impact on the economic and environmental performances of the supply chain. Balancing the trade-offs is critical to ensure the long-term sustainability. Originality/value The research offers many interesting observations with respect to the effect of product mix strategy on operational decisions and the trade-offs between costs and carbon emissions under the cap-and-trade policy. The insights derived from the analysis not only help firms to make important operational and strategic decisions to reduce carbon emissions while maintaining their economic competitiveness, but also make meaningful contribution to governments’ policy making for carbon emissions control.


2019 ◽  
Vol 3 (2) ◽  
pp. 110-130 ◽  
Author(s):  
Dave C. Longhorn ◽  
Joshua R. Muckensturm

Purpose This paper aims to introduce a new mixed integer programming formulation and associated heuristic algorithm to solve the Military Nodal Capacity Problem, which is a type of supply chain network design problem that involves determining the amount of capacity expansion required at theater nodes to ensure the on-time delivery of military cargo. Design/methodology/approach Supply chain network design, mixed integer programs, heuristics and regression are used in this paper. Findings This work helps analysts at the United States Transportation Command identify what levels of throughput capacities, such as daily processing rates of trucks and railcars, are needed at theater distribution nodes to meet warfighter cargo delivery requirements. Research limitations/implications This research assumes all problem data are deterministic, and so it does not capture the variations in cargo requirements, transit times or asset payloads. Practical implications This work gives military analysts and decision makers prescriptive details about nodal capacities needed to meet demands. Prior to this work, insights for this type of problem were generated using multiple time-consuming simulations often involving trial-and-error to explore the trade space. Originality/value This work merges research of supply chain network design with military theater distribution problems to prescribe the optimal, or near-optimal, throughput capacities at theater nodes. The capacity levels must meet delivery requirements while adhering to constraints on the proportion of cargo transported by mode and the expected payloads for assets.


Author(s):  
Jun Zhao ◽  
Lixiang Huang

The management of hazardous wastes in regions is required to design a multi-echelon network with multiple facilities including recycling, treatment and disposal centers servicing the transportation, recycling, treatment and disposal procedures of hazardous wastes and waste residues. The multi-period network design problem within is to determine the location of waste facilities and allocation/transportation of wastes/residues in each period during the planning horizon, such that the total cost and total risk in the location and transportation procedures are minimized. With consideration of the life cycle capacity of disposal centers, we formulate the problem as a bi-objective mixed integer linear programming model in which a unified modeling strategy is designed to describe the closing of existing waste facilities and the opening of new waste facilities. By exploiting the characteristics of the proposed model, an augmented ε -constraint algorithm is developed to solve the model and find highly qualified representative non-dominated solutions. Finally, computational results of a realistic case demonstrate that our algorithm can identify obviously distinct and uniformly distributed representative non-dominated solutions within reasonable time, revealing the trade-off between the total cost and total risk objectives efficiently. Meanwhile, the multi-period network design optimization is superior to the single-period optimization in terms of the objective quality.


Energies ◽  
2020 ◽  
Vol 13 (4) ◽  
pp. 782
Author(s):  
Na Zhang ◽  
Zijia Wang ◽  
Feng Chen ◽  
Jingni Song ◽  
Jianpo Wang ◽  
...  

There are increasing traffic pollution issues in the process of urbanization in many countries; urban rail transit is low-carbon and widely regarded as an effective way to solve such problems. The passenger flow proportion of different transportation types is changing along with the adjustment of the urban traffic structure and a growing demand from passengers. The reduction of carbon emissions brought about by rail transit lacks specific quantitative research. Based on a travel survey of urban residents, this paper constructed a method of estimating carbon emissions from two different scenarios where rail transit is and is not available. This study uses the traditional four-stage model to forecast passenger volume demand at the city level and then obtains the basic target parameters for constructing the carbon emission reduction model, including the trip origin-destination (OD), mode, and corresponding distance range of different modes on the urban road network. This model was applied to Baoji, China, where urban rail transit will be available from 2023. It calculates the changes in carbon emission that rail transit can bring about and its impact on carbon emission reductions in Baoji in 2023.


Author(s):  
Mohsen Varsei ◽  
Katherine Christ ◽  
Roger Burritt

Purpose Given that currently around ten billion litres of wine are transported long distances to overseas consumers per year, the purpose of this paper is to provide a foundation for understanding the trade-offs between cost, water usage and carbon emissions in decisions about the location of wine bottling plants in a global supply chain. Design/methodology/approach This paper presents a case-based analytical modelling study and employs actual data from one of Australia’s major wine companies. A descriptive analytical model is developed for assessing wine supply chain scenarios using three indicators of economic and environmental impacts – supply chain cost, risk-weighted water usage and carbon emissions. Findings The research highlights trade-offs required when considering optimal supply chain design, and finds possibilities for reshaping a global wine supply chain in order to improve the selected economic and environmental impacts. Originality/value The originality of this paper lies in its analytical focus on examining the interplay between supply chain cost, risk-weighted water usage and carbon emissions in a global supply chain, which has not previously been addressed.


2017 ◽  
Vol 28 (1) ◽  
pp. 127-149 ◽  
Author(s):  
Sajan T. John ◽  
Rajagopalan Sridharan ◽  
P.N. Ram Kumar

Purpose The purpose of this paper is to develop a mathematical model for the network design of a reverse supply chain in a multi-product, multi-period environment. The emission cost due to transportation activities is incorporated into the model to reduce the total cost of emission and study the significance of inclusion of emission cost on the network design decisions. Design/methodology/approach Mixed integer linear programming formulation is used to model the network. The developed model is solved and analysed using the commercial solver LINGO. Findings The mathematical model provides a unified design of the network for the entire planning horizon comprising of different periods. A reduction in the total cost of emission is achieved. The analysis of the problem environment shows that the network design decisions significantly vary with the consideration of emission cost. Research limitations/implications A single mode of transportation is considered in this study. Also, a single type of vehicle is considered for the transportation purpose. Practical implications The developed model can aid the decision makers in making better decisions while reducing the total emission cost. The quantification of the emission cost due to transportation activities is presented in an Indian context and can be used for future studies. Originality/value An all-encompassing approach for the design of reverse logistics networks with explicit consideration of product structure and emission cost.


2019 ◽  
Vol 7 (2) ◽  
pp. 102-115
Author(s):  
Zaher Hamad Alsalem ◽  
Ramkumar Harikrishnakumar ◽  
Vatsal Maru ◽  
Krishna Krishnan

The study of the effect of redistribution strategy and aggregation, on a multi-echelon supply chain network by managing demand volatility is discussed in this research. For this an operational supply chain design is considered. Multi-echelon network consisting of manufacturing plants, distribution centers, warehouses, and retailers is used to develop the case study. Aggregation strategy was analyzed in the context of single product and multi-product for a multi-period production problem under demand uncertainty. Product sourcing between echelons and distribution strategies are considered for the study. Objective was to use the redistribution strategy to optimize the objective functions for the network. The objective functions include minimization of total cost, minimization of overage and stock-out conditions, and maximization of the customer service level. The total cost function includes product flow, transportation cost and distance cost. The mathematical formulation is carried out in Mixed Integer Linear Programming (MILP) with the help of Generic Algebraic Modeling System (GAMS). Problem formulation considers three type of demand based on volatility and uncertainty cases as high, medium, and low. The research is divided into three main phases to discuss an optimal multi-echelon supply chain network for single product using aggregation strategy.


Sign in / Sign up

Export Citation Format

Share Document