scholarly journals Reverse Logistics Network Design and Simulation for Automatic Teller Machines Based on Carbon Emission and Economic Benefits: A Study of the Anhui Province ATMs Industry

2021 ◽  
Vol 13 (20) ◽  
pp. 11373
Author(s):  
Shouxu Song ◽  
Yongting Tian ◽  
Dan Zhou
Keyword(s):  
Objective Function ◽  
Reverse Logistics ◽  
Economic Benefits ◽  
Anhui Province ◽  
Mixed Integer ◽  
Logistics Network ◽  
Calculation Results ◽  
Milp Model ◽  
Automatic Teller Machines ◽  
Surrounding Areas

In recent years, mobile payments have gradually replaced cash payments, resulting in a gradual decline in the number of automatic teller machines (ATMs) demanded by banks. Through investigation and analysis, we determine four means to deal with decommissioned ATMs, and construct thereafter an ATM reverse logistics (RL_ATMs) network model, which includes suppliers, producers, warehouses, operators, maintenance centers, collection and inspection centers, disposal centers, remanufacturing centers, and recycling centers. This model is further expressed as a mixed integer linear programming (MILP) model. Given that an ATM recycling network has planned and batched characteristics, a percentage diversion method is proposed to transform a real multi-cycle problem to a single-cycle problem. The RL_ATMs network constructed in this study presents the two forms of ATMs, functional modules and the entire machine. We used the actual situations of the related companies and enterprises in Anhui Province and its surrounding areas, as well as major banks’ ATMs, as bases in using the LINGO software to solve the proposed MILP model with the objective function of minimizing costs and environmental emissions, and obtain the relevant companies’ launch operations. Lastly, we analyzed the relationship between coefficients in the percentage diversion method and calculation results, cost, and carbon emissions. Accordingly, we find that the number of remanufacturing and maintenance centers has no evident impact on the objective function, transportation costs account for a large proportion of the total cost, and emissions tax is small.

A mixed-integer linear programming approach for circular economy-led closed-loop supply chains in green reverse logistics network design under uncertainty

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Kazhal Gharibi ◽  
Sohrab Abdollahzadeh
Keyword(s):  
Linear Programming ◽  
Objective Function ◽  
Integer Linear Programming ◽  
Reverse Logistics ◽  
Mixed Integer Linear Programming ◽  
Closed Loop ◽  
Mixed Integer ◽  
Content Type ◽  
Logistics Network ◽  
Reverse Logistics Network

PurposeTo maximize the network total profit by calculating the difference between costs and revenue (first objective function). To maximize the positive impact on the environment by integrating GSCM factors in RL (second objective function). To calculate the efficiency of disassembly centers by SDEA method, which are selected as suppliers and maximize the total efficiency (third objective function). To evaluate the resources and total efficiency of the proposed model to facilitate the allocation resource process, to increase resource efficiency and to improve the efficiency of disassembly centers by Inverse DEA.Design/methodology/approachThe design of a closed-loop logistics network for after-sales service for mobile phones and digital cameras has been developed by the mixed-integer linear programming method (MILP). Development of MILP method has been performed by simultaneously considering three main objectives including: total network profit, green supply chain factors (environmental sustainability) and maximizing the efficiency of disassembly centers. The proposed model of study is a six-level, multi-objective, single-period and multi-product that focuses on electrical waste. The efficiency of product return centers is calculated by SDEA method and the most efficient centers are selected.FindingsThe results of using the model in a case mining showed that, due to the use of green factors in network design, environmental pollution and undesirable disposal of some electronic waste were reduced. Also, with the reduction of waste disposal, valuable materials entered the market cycle and the network profit increased.Originality/value(1) Design a closed-loop reverse logistics network for after-sales services; (2) Introduce a multi-objective multi-echelon mixed integer linear programming model; (3) Sensitivity analysis use Inverse-DEA method to increase the efficiency of inefficient units; (4) Use the GSC factors and DEA method in reverse logistics network.

scholarly journals Reverse Logistics Network Design of Electric Vehicle Batteries considering Recall Risk

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Hao Hao ◽  
Yichen Sun ◽  
Xueyun Mei ◽  
Yanjun Zhou
Keyword(s):  
Environmental Pollution ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Reverse Logistics ◽  
Economic Benefits ◽  
Environmental Risks ◽  
Sales Volume ◽  
Logistics Network ◽  
The Social ◽  
Reverse Logistics Network

In 2018-2019, the recall scale of electric vehicles (EVs) in China reached 168,700 units; recalls account for approximately 6.9% of sales volume. There are imperative reasons for electric vehicle batteries (EVBs) recalls, such as mandatory laws or policies, safety and environmental pollution risks, and the high value of EVB echelon use, and thus, it has become increasingly important to reasonably design a reverse logistics (RL) network for an EVB recall. In this study, a multiobjective and multiperiod recall RL network model is developed to minimize safety and environmental risks, maximize the social responsibility and economic benefits, and consider the characteristics of EVBs, including the configuration of key recall facilities and the control of recall flows. The results of this study will help EVB practitioners, relevant departmental policymakers, and others to comprehensively understand the recall of EVBs, strengthen the safety and environmental protection issues in the EVB recall process, and promote the establishment of a safe, green, and sustainable EVB recall RL network.

scholarly journals How to Effectively Improve Pesticide Waste Governance: A Perspective of Reverse Logistics

2018 ◽  
Vol 10 (10) ◽  
pp. 3622 ◽  
Author(s):  
Zhichao Li ◽  
Jilin Huang
Keyword(s):  
Network Model ◽  
Reverse Logistics ◽  
Empirical Studies ◽  
Modern Science ◽  
Flow Distribution ◽  
Network Models ◽  
Mixed Integer ◽  
Treatment Center ◽  
Logistics Network ◽  
Reverse Logistics Network

With the development of modern science and technology, agricultural production and quality have made major breakthroughs, followed by more and more pesticide waste. Pesticide waste refers to the packaging of pesticide residues. Pesticide waste will cause great damage to soil, water and human health, seriously affecting the ecological sustainability. Most of the existing literature is theoretical articles, and few empirical studies are provided on how to improve pesticide waste management. In this paper, a set of reverse logistics network models of pesticide wastes is constructed, and the framework of reverse logistics is used to realize the efficient recovery and treatment of pesticide wastes. The problem of how to collect pesticide wastes and how to optimize the location and flow allocation of facilities such as recycling center and treatment center was solved. The weights of the factors affecting the reverse logistics network model are determined by using the network analytic hierarchy process. Under the conditions of minimizing the cost and minimizing the negative externality, the mixed integer model programming method is used to make the optimal location decision and flow distribution. Finally, taking the JT area of China as an example, the results of the reverse logistics network model of pesticide wastes are demonstrated. The results show that the scheme is feasible.

scholarly journals Accelerated Benders’ Decomposition for Integrated Forward/Reverse Logistics Network Design under Uncertainty

2017 ◽  
Author(s):  
Vahab Vahdat ◽  
Mohammad Ali vahdatzad
Keyword(s):  
Network Design ◽  
Reverse Logistics ◽  
Valid Inequalities ◽  
Network Design Problem ◽  
Mixed Integer ◽  
Master Problem ◽  
Test Problems ◽  
Distribution Centers ◽  
Logistics Network ◽  
Reverse Logistics Network

In this paper, a two-stage stochastic programming modelling is proposed to design a multi-period, multistage, and single-commodity integrated forward/reverse logistics network design problem under uncertainty. The problem involves both strategic and tactical decision levels. The first stage deals with strategic decisions, which are the number, capacity, and location of forward and reverse facilities. At the second stage tactical decisions such as base stock level as an inventory policy is determined. The generic introduced model consists of suppliers, manufactures, and distribution centers in forward logistic and collection centers, remanufactures, redistribution, and disposal centers in reverse logistic. The strength of proposed model is its applicability to various industries. The problem is formulated as a mixed-integer linear programming model and is solved by using Benders’ Decomposition (BD) approach. In order to accelerate the Benders’ decomposition, a number of valid inequalities are added to the master problem. The proposed accelerated BD is evaluated through small-, medium-, and large-sized test problems. Numerical results reveal that proposed solution algorithm increases convergence of lower bound and upper bound of BD and is able to reach an acceptable optimality gap in a convenient CPU time.

scholarly journals Reverse Logistics Network Optimizing by Genetic Algorithm: A Case Study of Automotive Wiring Harnesses

2014 ◽  
Vol 564 ◽  
pp. 740-746 ◽  
Author(s):  
Abdolhossein Sadrnia ◽  
N. Ismail ◽  
M.K.A.M. Ariffin ◽  
Zulkifli Norzima ◽  
Omid Boyer
Keyword(s):  
Genetic Algorithm ◽  
Reverse Logistics ◽  
Programming Model ◽  
Mixed Integer ◽  
Profit Model ◽  
Logistics Network ◽  
Wiring Harness ◽  
Reverse Logistics Network ◽  
Optimum Solution

The shortage of material and environmental legislations have encouraged car manufacturers to recycle used material in end of life vehicles (ELVs), reverse logistics are essential to the concerns of the automotive supply chain. In this research, a profit model multi-echelon reverse logistics network including collection center, shredder center and recycling center is developed to recycle automotive parts. The work was continued by illustrating empirical application in wiring harness manufacturer that would like to recycle wire harnesses and extract copper. With regards to the complexity of the reverse logistics network, traditional method cannot be implemented for solving them. Thus, an evolutionary algorithm based genetic algorithm (GA) is applied as a solution methodology to solve mixed integer linear programming model and find the optimum solution. The results emphasize the efficiency of the modeling and solving method so that in the case study the company gained more than 27 thousand dollars through the establishment of reverse logistics for recycling copper.

scholarly journals A Multi-objective MILP Model Proposed to Optimize a Supply Chain Network for Microalgae-based Biofuels and Co-products: A Case Study in Iran

2021 ◽  
Author(s):  
Mohammad Ehsan Zerafati ◽  
Ali Bozorgi-Amiri ◽  
Amir-Mohammad Golmohammadi ◽  
Fariborz Jolai
Keyword(s):  
Supply Chain ◽  
Objective Function ◽  
Environmental Impacts ◽  
Deterministic Model ◽  
Mixed Integer ◽  
Supply Chain Network ◽  
Multi Objective ◽  
Proposed Model ◽  
Milp Model

Abstract Recently, due to the efficiency of cultivating microalgae, researchers and investors have paid considerable attention to the production of different biofuel products that are environmentally friendly. In this study, a two-stage deterministic model is proposed to design a microalgae-based biofuels and co-products supply chain network (MBCSCN). In the first stage, the appropriate locations for the cultivation of microalgae are identified through the analytical hierarchy process (AHP). In the second stage, a deterministic mathematical mixed integer linear programing (MILP) model is developed for a period of five years based on the criteria of economic and environmental impacts. The economic objective function maximizes the overall profit, while the environmental impacts objective function seeks to minimize the consumed fossil fuel throughout the supply chain. Then, a multi-objective MILP optimization problem is solved using the ε-constraint method. The proposed model is evaluated through a case study in Iran. It has helped to identify appropriate locations for the cultivation of microalgae and to specify the required quantity of feedstock, the species of microalgae, the required technology, and the transportation modes in each step of the supply chain.

scholarly journals Reverse Logistics Network Design for Effective Management of Medical Waste in Epidemic Outbreaks: Insights from the Coronavirus Disease 2019 (COVID-19) Outbreak in Wuhan (China)

2020 ◽  
Vol 17 (5) ◽  
pp. 1770 ◽  
Author(s):  
Hao Yu ◽  
Xu Sun ◽  
Wei Deng Solvang ◽  
Xu Zhao
Keyword(s):  
Network Design ◽  
Reverse Logistics ◽  
Medical Waste ◽  
Mixed Integer ◽  
Effective Management ◽  
Human Beings ◽  
Epidemic Disease ◽  
Logistics Network ◽  
Short Period ◽  
Reverse Logistics Network

The outbreak of an epidemic disease may pose significant treats to human beings and may further lead to a global crisis. In order to control the spread of an epidemic, the effective management of rapidly increased medical waste through establishing a temporary reverse logistics system is of vital importance. However, no research has been conducted with the focus on the design of an epidemic reverse logistics network for dealing with medical waste during epidemic outbreaks, which, if improperly treated, may accelerate disease spread and pose a significant risk for both medical staffs and patients. Therefore, this paper proposes a novel multi-objective multi-period mixed integer program for reverse logistics network design in epidemic outbreaks, which aims at determining the best locations of temporary facilities and the transportation strategies for effective management of the exponentially increased medical waste within a very short period. The application of the model is illustrated with a case study based on the outbreak of the coronavirus disease 2019 (COVID-19) in Wuhan, China. Even though the uncertainty of the future COVID-19 spread tendency is very high at the time of this research, several general policy recommendations can still be obtained based on computational experiments and quantitative analyses. Among other insights, the results suggest installing temporary incinerators may be an effective solution for managing the tremendous increase of medical waste during the COVID-19 outbreak in Wuhan, but the location selection of these temporary incinerators is of significant importance. Due to the limitation on available data and knowledge at present stage, more real-world information are needed to assess the effectiveness of the current solution.

scholarly journals Research on SKINNY Optimal Differential Trail Search

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Shaoqiang Liu ◽  
Chaiyang Peng ◽  
Chunjiang Li
Keyword(s):  
Objective Function ◽  
Mixed Integer ◽  
Programming Algorithm ◽  
Differential Probability ◽  
Linear Programming Algorithm ◽  
Round Number ◽  
Differential Characteristic ◽  
Minimum Number ◽  
Lightweight Block Cipher ◽  
Milp Model

SKINNY is a tweakable lightweight block cipher algorithm. In order to test its security, this paper performs optimal differential trail search analysis on all SKINNY-64 versions under single-key setting based on the MILP (Mixed Integer Linear Programming) algorithm. Firstly, SKINNY round function is abstracted equivalently by precise constraints, and the objective function is set as the minimum number of active S-box number to optimize SKINNY-64 MILP model. Experiments show the differential trail searched by this method is not necessarily optimal. In order to directly search for the optimal differential trail, the S-box differential probability coding information is added to the optimized SKINNY-64 MILP model, the S-box differential characteristic is reconstructed, and the objective function is set to the minimum value of the probability coding information, which improves the SKINNY-64 MILP model. The results of experimental show that the improved MILP model can directly search for the optimal differential trail, and the complexity is slightly increased, but the search efficiency is significantly improved. Under single-key setting, this method has obvious advantage in searching the optimal differential trails of SKINNY-64 with low round number.

Literature Review and Prospect on the End-of-Life Vehicles Reverse Logistics

2014 ◽  
Vol 878 ◽  
pp. 66-74 ◽  
Author(s):  
Jun Wei Gan ◽  
Zheng Gang He
Keyword(s):  
End Of Life ◽  
Reverse Logistics ◽  
Renewable Resource ◽  
Economic Benefits ◽  
Research Field ◽  
Future Research ◽  
Logistics System ◽  
Logistics Network ◽  
Reverse Logistics Network ◽  
The Status

End-of-life vehicles (ELVs), as an important renewable resource, have huge environmental and economic benefits. In recent years, with the rapid growth of the number of ELVs, ELV reverse logistics is becoming a hot research field. In this paper, the overall trend of ELV reverse logistics research at home and abroad and a review of the status quo and countermeasures of ELV recycling, the choice of recycling mode, the ELV reverse logistics system and the reverse logistics network are presented. Finally, on the basis of performed review, some recommendations for the future research are discussed.

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