scholarly journals Risk-Averse Co-Decision for Lower-Carbon Product Family Configuration and Resilient Supplier Selection

2021 ◽  
Vol 14 (1) ◽  
pp. 384
Author(s):  
Dengzhuo Liu ◽  
Zhongkai Li ◽  
Chao He ◽  
Shuai Wang
Keyword(s):  
Supply Chain ◽  
Supplier Selection ◽  
Programming Model ◽  
Ghg Emissions ◽  
Product Family ◽  
Mixed Integer ◽  
Risk Averse ◽  
Worst Case ◽  
Risk Neutral ◽  
Disruption Risks

Due to global pandemics, political unrest and natural disasters, the stability of the supply chain is facing the challenge of more uncertain events. Although many scholars have conducted research on improving the resilience of the supply chain, the research on integrating product family configuration and supplier selection (PCSS) under disruption risks is limited. In this paper, the centralized supply chain network, which contains only one major manufacturer and several suppliers, is considered, and one resilience strategy (i.e., the fortified supplier) is used to enhance the resilience level of the selected supply base. Then, an improved stochastic bi-objective mixed integer programming model is proposed to support co-decision for PCSS under disruption risks. Furthermore, considering the above risk-neutral model as a benchmark, a risk-averse mixed integer program with Conditional Value-at-Risk (CVaR) is formulated to achieve maximum potential worst-case profit and minimum expected total greenhouse gases (GHG) emissions. Then, NSGA-II is applied to solve the proposed stochastic bi-objective mixed integer programming model. Taking the electronic dictionary as a case study, the risk-neutral solutions and risk-averse solutions that optimize, respectively, average and worst-case objectives of co-decision are also compared under two different ranges of disruption probability. The sensitivity analysis on the confidence level indicates that fortifying suppliers and controlling market share in co-decision for PCSS can effectively reduce the risk of low-profit/high-cost while minimizing the expected GHG emissions. Meanwhile, the effects of low-probability risk are more likely to be ignored in the risk-neutral solution, and it is necessary to adopt a risk-averse solution to reduce potential worst-case losses.

scholarly journals Local Blood Supply Chain Optimization: A Case Study

2020 ◽  
Vol 18 (4) ◽  
Author(s):  
Reza Babazadeh ◽  
Ali Sabbaghnia ◽  
Fatemeh Shafipour
Keyword(s):  
Supply Chain ◽  
Blood Supply ◽  
Blood Donation ◽  
Programming Model ◽  
Human Life ◽  
Mixed Integer ◽  
Model Parameters ◽  
Supply Chain Optimization ◽  
Blood Supply Chain ◽  
Proposed Model

: Blood and its products play an undeniable role in human life. In recent years, although both academics and practitioners have investigated blood-related problems, further enhancement is still warranted. In this study, a mixed-integer linear programming model was proposed for local blood supply chain management. A supply network, including temporary and fixed blood donation facilities, blood banks, and blood processing centers, was designed regarding the deteriorating nature of blood. The proposed model was applied in a real case in Urmia, Iran. The numerical results and sensitivity analysis of the key model parameters ensured the applicability of the proposed model.

scholarly journals Supply chain optimization with variable demand by considering financial criteria and scenarios

2017 ◽  
Vol 26 (44) ◽  
pp. 21 ◽  
Author(s):  
John Willmer Escobar
Keyword(s):  
Supply Chain ◽  
Large Scale ◽  
Net Present Value ◽  
Programming Model ◽  
Supply Chain Design ◽  
Mixed Integer ◽  
Supply Network ◽  
Distribution Centers ◽  
Supply Chain Optimization ◽  
Starting Point

This paper contemplates the supply chain design problem of a large-scale company by considering the maximization of the Net Present Value. In particular, the variability of the demand for each type of product at each customer zone has been estimated. As starting point, this paper considers an established supply chain for which the main problem is to determine the decisions regarding expansion of distribution centers. The problem is solved by using a mixed-integer linear programming model, which optimizes the different demand scenarios. The proposed methodology uses a scheme of optimization based on the generation of multiple demand scenarios of the supply network. The model is based on a real case taken from a multinational food company, which supplies to the Colombian and some international markets. The obtained results were compared with the equivalent present costs minimization scheme of the supply network, and showed the importance and efficiency of the proposed approach as an alternative for the supply chain design with stochastic parameters.

scholarly journals Interactive Fuzzy Multi Criteria Decision Making Approach for Supplier Selection and Order Allocation in a Resilient Supply Chain

Mathematics ◽  
2019 ◽  
Vol 7 (2) ◽  
pp. 137 ◽  
Author(s):  
Sonia Mari ◽  
Muhammad Memon ◽  
Muhammad Ramzan ◽  
Sheheryar Qureshi ◽  
Muhammad Iqbal
Keyword(s):  
Supply Chain ◽  
Supplier Selection ◽  
Fuzzy Optimization ◽  
Order Allocation ◽  
Supply Networks ◽  
Supply Chain Resilience ◽  
Fuzzy Environment ◽  
Selection Decisions ◽  
Low Probability ◽  
Disruption Risks

Modern supply chains are vulnerable to high impact, low probability disruption risks. A supply chain usually operates in such a network of entities where the resilience of one supplier is critical to overall supply chain resilience. Therefore, resilient planning is a key strategic requirement in supplier selection decisions for a competitive supply chain. The aim of this research is to develop quantitative resilient criteria for supplier selection and order allocation in a fuzzy environment. To serve the purpose, a possibilistic fuzzy multi-objective approach was proposed and an interactive fuzzy optimization solution methodology was developed. Using the proposed approach, organizations can tradeoff between cost and resilience in supply networks. The approach is illustrated using a supply chain case from a garments manufacturing company.

The PHEV Charging Infrastructure Planning (PCIP) Problem

2010 ◽  
Vol 11 (2) ◽  
Author(s):  
Yogesh Dashora ◽  
John W Barnes ◽  
Rekha S Pillai ◽  
Todd E Combs ◽  
Michael Hilliard ◽  
...  
Keyword(s):  
Programming Model ◽  
National Laboratory ◽  
Ghg Emissions ◽  
Geographic Location ◽  
Mixed Integer ◽  
Infrastructure Planning ◽  
Charging Infrastructure ◽  
Oak Ridge ◽  
Charging Station ◽  
First Time

Increasing debates over a gasoline independent future and the reduction of greenhouse gas (GHG) emissions has led to a surge in plug-in hybrid electric vehicles (PHEVs) being developed around the world. The majority of PHEV related research has been directed at improving engine and battery operations, studying future PHEV impacts on the grid, and projecting future PHEV charging infrastructure requirements. Due to the limited all-electric range of PHEVs, a daytime PHEV charging infrastructure will be required for most PHEV daily usage. In this paper, for the first time, we present a mixed integer mathematical programming model to solve the PHEV charging infrastructure planning (PCIP) problem for organizations with thousands of people working within a defined geographic location and parking lots well suited to charging station installations. Our case study, based on the Oak Ridge National Laboratory (ORNL) campus, produced encouraging results, indicates the viability of the modeling approach and substantiates the importance of considering both employee convenience and appropriate grid connections in the PCIP problem.

scholarly journals Coordinating Contracts for Two-Stage Fashion Supply Chain with Risk-Averse Retailer and Price-Dependent Demand

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Minli Xu ◽  
Qiao Wang ◽  
Linhan Ouyang
Keyword(s):  
Supply Chain ◽  
Supply Chain Coordination ◽  
Revenue Sharing ◽  
Channel Coordination ◽  
Risk Averse ◽  
Revenue Sharing Contract ◽  
Risk Neutral ◽  
Mean Variance ◽  
Variance Approach ◽  
Dependent Demand

When the demand is sensitive to retail price, revenue sharing contract and two-part tariff contract have been shown to be able to coordinate supply chains with risk neutral agents. We extend the previous studies to consider a risk-averse retailer in a two-echelon fashion supply chain. Based on the classic mean-variance approach in finance, the issue of channel coordination in a fashion supply chain with risk-averse retailer and price-dependent demand is investigated. We propose both single contracts and joint contracts to achieve supply chain coordination. We find that the coordinating revenue sharing contract and two-part tariff contract in the supply chain with risk neutral agents are still useful to coordinate the supply chain taking into account the degree of risk aversion of fashion retailer, whereas a more complex sales rebate and penalty (SRP) contract fails to do so. When using combined contracts to coordinate the supply chain, we demonstrate that only revenue sharing with two-part tariff contract can coordinate the fashion supply chain. The optimal conditions for contract parameters to achieve channel coordination are determined. Numerical analysis is presented to supplement the results and more insights are gained.

Model of Supply Chain Disruption Risk Defense System

2014 ◽  
Vol 511-512 ◽  
pp. 1239-1243
Author(s):  
Han Qing Li ◽  
Yi Hong Ru
Keyword(s):  
Supply Chain ◽  
Integer Programming ◽  
Location Problem ◽  
Programming Model ◽  
Facility Location Problem ◽  
Mixed Integer ◽  
Defense System ◽  
Supply Chain Risk ◽  
Supply Chain Disruption ◽  
Disruption Risk

This study is comprised of three main problems. Firstly, a supply chain risk defense problem (SCRDP) is proposed. Then, the study considers a facility location problem in the presence of random facility disruptions where the facilities can be defensed with additional investments. It is formulated as a mixed integer programming model. Finally, a case shows a location solution which designs how to distribute the hardened and non-hardened facilities.

scholarly journals The effects of different kinds of returns on an integrated chance-constrained stochastic mobile phone closed-loop supply chain configuration and supplier selection

2021 ◽  
Author(s):  
Shahrzad Ahmadi Kermanshah
Keyword(s):  
Supply Chain ◽  
Mobile Phone ◽  
Supplier Selection ◽  
Closed Loop ◽  
Stochastic Demand ◽  
Mixed Integer ◽  
Chance Constraint ◽  
Distance Method ◽  
Closed Loop Supply Chain ◽  
Multi Objective

One of the important concerns in the world is E-waste. Ending up e-waste in the landfill and inappropriate disposing of it are hazardous to the environment. The goal of this research is to design and optimize a multi-period, multi-product, multi-echelon, and multi-customer Closed-Loop Supply Chain (CLSC) network for a mobile phone network considering different types of product returns. Commercial, end of life, and end-of-use returns are well-known in practice. In this research, a multi-objective mixed-integer linear programming formulation with stochastic demand and return is proposed to maximize the total profit in the mobile phone CLSC network, alongside maximizing the weights of eligible suppliers which are estimated based on a fuzzy method for efficient supplier selection and order allocation. Chance-constraint programming is applied in order to deal with the stochastic demand and return. Moreover, distance method and εε-constraint technique are employed to solve the proposed multi-objective problem. The application of the proposed mathematical model is illustrated in Toronto, Canada using real maps.

Sign in / Sign up

Export Citation Format

Share Document