Multi-period reverse logistics network design with emission cost

2017 ◽  
Vol 28 (1) ◽  
pp. 127-149 ◽  
Author(s):  
Sajan T. John ◽  
Rajagopalan Sridharan ◽  
P.N. Ram Kumar
Keyword(s):  
Mathematical Model ◽  
Network Design ◽  
Reverse Logistics ◽  
Planning Horizon ◽  
Mixed Integer ◽  
Single Type ◽  
Reverse Supply Chain ◽  
Design Decisions ◽  
Content Type ◽  
Total Cost

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.

scholarly journals Multi-Period Network Design Problem in Regional Hazardous Waste Management Systems

2019 ◽  
Vol 16 (11) ◽  
pp. 2042 ◽  
Author(s):  
Jun Zhao ◽  
Lixiang Huang
Keyword(s):  
Network Design ◽  
Design Problem ◽  
Programming Model ◽  
Planning Horizon ◽  
Network Design Problem ◽  
Mixed Integer ◽  
Hazardous Wastes ◽  
Total Risk ◽  
Total Cost ◽  
Treatment And Disposal

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.

Modelling and analysis of network design for a reverse supply chain

2015 ◽  
Vol 26 (6) ◽  
pp. 853-867 ◽  
Author(s):  
Sajan T John ◽  
R Sridharan
Keyword(s):  
Supply Chain ◽  
Network Design ◽  
Input Parameter ◽  
Mixed Integer ◽  
Future Research ◽  
Data Sets ◽  
Reverse Supply Chain ◽  
Content Type ◽  
Product Return ◽  
Multi Stage

Purpose – The purpose of this paper is to develop a mathematical model for the design of a multi-stage reverse supply chain. Design/methodology/approach – A mixed-integer linear programming formulation is used to model the network. Different data sets are generated randomly. Lingo, an optimisation package is used to solve the model developed. Findings – The model is able to provide optimum solutions regarding the number and location of different facilities to be established in the network. The flow of different items through the network is also obtained. Analysis of the results shows the sensitivity of design decisions with respect to the changes in the input parameter value. Research limitations/implications – The authors consider only a single-product and single-period situation for this study. Further research can be done by considering a multi-product and multi-period situation. Uncertainty in data can also be included for future research. Practical implications – The developed model can aid the managers in taking optimum decisions regarding the network design of a reverse supply chain. The analysis of the model for the variations in the input parameter values can also help the decision makers to take better decisions in a reverse supply chain. Originality/value – The present research simultaneously considers two types of product return, namely, end-of-life and end-of-use product return, in a seven stage supply chain. Different recovery options such as recycling and remanufacturing are also incorporated into the model.

scholarly journals Maximizing Profit in Reverse Supply Chain

2015 ◽  
Vol 8 (11) ◽  
pp. 111 ◽  
Author(s):  
Ehsan Khansalar ◽  
Mahmood Lari Dashte Bayaz ◽  
Reza Safari
Keyword(s):  
Mathematical Model ◽  
Supply Chain ◽  
Analytical Model ◽  
Reverse Logistics ◽  
Production Costs ◽  
Reverse Supply Chain ◽  
Total Cost ◽  
Logistics Network ◽  
Reverse Logistics Network ◽  
Production Strategies

<p>We try to find a linear analytical model to evaluate cost maximization using reverse logistics network in recycle industry, which reduces total cost of reverse logistics. In industries that production costs or percentage of recurred goods are significantly high, reverse logistics is so important. The purpose of this research is presenting a reverse logistics model and also a mathematical model to minimize costs and maximize benefits in recycle industry. Presented model in this research is a multi-variable system which has some constraints. This model helps organizations to use appropriate production strategies.</p>

scholarly journals A Multi-Echelon Network Design in a Dual-Channel Reverse Supply Chain Considering Consumer Preference

2021 ◽  
Vol 18 (9) ◽  
pp. 4760
Author(s):  
Peng Li ◽  
Di Wu
Keyword(s):  
Supply Chain ◽  
Network Design ◽  
Environmental Sustainability ◽  
Rapid Development ◽  
Consumer Preference ◽  
Service Level ◽  
Mixed Integer ◽  
Reverse Supply Chain ◽  
Related Factors ◽  
Dual Channel

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.

Environmentally sustainable stochastic procurement model

2018 ◽  
Vol 29 (3) ◽  
pp. 472-498 ◽  
Author(s):  
Harpreet Kaur ◽  
Surya Prakash Singh
Keyword(s):  
Carbon Emissions ◽  
Environmental Sustainability ◽  
Lot Sizing ◽  
Planning Horizon ◽  
Business Environment ◽  
Manufacturing Firms ◽  
Mixed Integer ◽  
Content Type ◽  
Environmentally Sustainable ◽  
Procurement Planning

Purpose Procurement planning has always been a huge and challenging activity for business firms, especially in manufacturing. With government legislations about global concern over carbon emissions, the manufacturing firms are enforced to regulate and reduce the emissions caused throughout the supply chain. It is observed that procurement and logistics activities in manufacturing firms contribute heavily toward carbon emissions. Moreover, highly dynamic and uncertain business environment with uncertainty in parameters such as demand, supplier and carrier capacity adds to the complexity in procurement planning. The paper aims to discuss these issues. Design/methodology/approach This paper is a novel attempt to model environmentally sustainable stochastic procurement (ESSP) problem as a mixed-integer non-linear program. The ESSP optimizes the procurement plan of the firm including lot-sizing, supplier and carrier selection by addressing uncertainty and environmental sustainability. The model applies chance-constrained-based approach to address the uncertain parameters. Findings The proposed ESSP model is solved optimally for 30 data sets to validate the proposed ESSP and is further demonstrated using three illustrations solved optimally in LINGO 10. Originality/value The ESSP model simultaneously minimizes total procurement cost and carbon emissions over the entire planning horizon considering uncertain demand, supplier and carrier capacity.

scholarly journals Determining nodal capacities for military distribution problems

2019 ◽  
Vol 3 (2) ◽  
pp. 110-130 ◽  
Author(s):  
Dave C. Longhorn ◽  
Joshua R. Muckensturm
Keyword(s):  
Supply Chain ◽  
Network Design ◽  
The United States ◽  
Network Design Problem ◽  
Mixed Integer ◽  
Multiple Time ◽  
Supply Chain Network Design ◽  
Supply Chain Network ◽  
Content Type ◽  
Distribution Problems

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.

Vehicle routing analyses with integrated order picking and delivery problem under carbon cap and trade policy

2019 ◽  
Vol 43 (2) ◽  
pp. 223-243 ◽  
Author(s):  
Sanjay Jharkharia ◽  
Chiranjit Das
Keyword(s):  
Sensitivity Analysis ◽  
Trade Policy ◽  
Vehicle Routing ◽  
Carbon Footprint ◽  
Order Picking ◽  
Mixed Integer ◽  
Vehicle Speed ◽  
Cap And Trade ◽  
Content Type ◽  
Total Cost

Purpose The purpose of this study is to model a vehicle routing problem with integrated picking and delivery under carbon cap and trade policy. This study also provides sensitivity analyses of carbon cap and price to the total cost. Design/methodology/approach A mixed integer linear programming (MILP) model is formulated to model the vehicle routing with integrated order picking and delivery constraints. The model is then solved by using the CPLEX solver. Carbon footprint is estimated by a fuel consumption function that is dependent on two factors, distance and vehicle speed. The model is analyzed by considering 10 suppliers and 20 customers. The distance and vehicle speed data are generated using simulation with random numbers. Findings Significant amount of carbon footprint can be reduced through the adoption of eco-efficient vehicle routing with a marginal increase in total transportation cost. Sensitivity analysis indicates that compared to carbon cap, carbon price has more influence on the total cost. Research limitations/implications The model considers mid-sized problem instances. To analyze large size problems, heuristics and meta-heuristics may be used. Practical implications This study provides an analysis of carbon cap and price model that would assist practitioners and policymakers in formulating their policy in the context of carbon emissions. Originality/value This study provides two significant contributions to low carbon supply chain management. First, it provides a vehicle routing model under carbon cap and trade policy. Second, it provides a sensitivity analysis of carbon cap and price in the model.

An integrated mathematical model of dynamic production and maintenance planning in pumped-storage hydroelectricity

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Farid Asgari ◽  
Fariborz Jolai ◽  
Farzad Movahedisobhani
Keyword(s):  
Mathematical Model ◽  
Exact Solution ◽  
Energy Production ◽  
Programming Model ◽  
Mixed Integer ◽  
Test Problems ◽  
Production Network ◽  
Content Type ◽  
The Difference ◽  
Pumped Storage

Purpose Pumped-storage hydroelectricity (PSH) is considered as an effective method to moderate the difference in demand and supply of electricity. This study aims to understanding of the high capacity of energy production, storage and permanent exploitation has been the prominent feature of pumped-storage hydroelectricity. Design/methodology/approach In this paper, the optimization of energy production and maintenance costs in one of the large Iranian PSH has been discussed. Hence, a mathematical model mixed integer nonlinear programming developed in this area. Minimizing the difference in supply and demand in the energy production network to multiple energies has been exploited to optimal attainment scheme. To evaluate the model, exact solution CPLEX and to solve the proposed programming model, the efficient metaheuristics are utilized by the tuned parameters achieved from the Taguchi approach. Further analysis of the parameters of the problem is conducted to verify the model behavior in various test problems. Findings The results of this paper have shown that the meta-heuristic algorithm has been done in a suitable time, despite the approximation of the optimal answer, and the consequences of research indicate that the model proposed in the studied power plant is applicable. Originality/value In pumped-storage hydroelectricity plants, one of the main challenges in energy production issues is the development of production, maintenance and repair scheduling concepts that improves plant efficiency. To evaluate the mathematical model presented, exact solution CPLEX and to solve the proposed bi-objective mixed-integer linear programming model, set of efficient metaheuristics are used. Therefore, according to the level of optimization performed in the case study, it has caused the improvement of planning by 7%–12% and effective optimization processes.

Modelling of sharing networks in the circular economy

2020 ◽  
Vol 15 (2) ◽  
pp. 407-440
Author(s):  
Jaivignesh Jayakumar ◽  
Jayakrishna K. ◽  
Vimal K.E.K. ◽  
Sawarni Hasibuan
Keyword(s):  
Mathematical Model ◽  
Environmental Impact ◽  
Circular Economy ◽  
Production System ◽  
Economic Benefit ◽  
Programming Model ◽  
Sharing Economy ◽  
Consumer Electronics ◽  
Mixed Integer ◽  
Content Type

Purpose The purpose of this paper is to develop and optimize a mathematical model based on a framework that integrates key concepts related to a circular economy (CE) and sharing economy (SE) for a leading manufacturer of laptops in India. Design/methodology/approach This study mathematically modelled the integration of sharing networks in a circular production system. This is done through an optimization package that deploys a multi-objective mixed-integer linear programming model. Findings This study evaluated the economic benefit and the environmental impact associated with the aforementioned integration in a production system. This study illustrated the inverse relationship between economic benefit and environmental impact and provided a set of solutions that can be used according to the case organizations goals, capacities and logistical capabilities. Research limitations/implications This study will aid similarly structured companies in adopting this approach to integrate sustainable practices in their production system. It also enumerated Industry 4.0 (I4.0) use-cases that can be used to effectively implement this mathematical model. Further research can be conducted using multiple companies in an inter-dependent network to maximize synergy. Practical implications This study will help to better understand the role of sharing networks in the circular economy model especially in the consumer electronics industry. Originality/value This study is the first of its kind to mathematically model the integration of aspects related to SE and CE. It also validates the aforementioned model using a numerical case-study and offers decision-support to key executives within the case organization.

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