scholarly journals Optimal Periodic Flexible Policies for Two-Stage Serial Supply Chains

2017 ◽  
Author(s):  
Fang Liu ◽  
Srinagesh Gavirneni
Keyword(s):  
Supply Chains ◽  
Two Stage ◽  
Serial Supply Chains

scholarly journals Revisiting the value of information sharing in two-stage supply chains

2018 ◽  
Vol 270 (3) ◽  
pp. 1044-1052 ◽  
Author(s):  
Ruud H. Teunter ◽  
M. Zied Babai ◽  
Jos A.C. Bokhorst ◽  
Aris A. Syntetos
Keyword(s):  
Supply Chains ◽  
Information Sharing ◽  
Value Of Information ◽  
Two Stage

Sustainably resilient supply chains evaluation in public transport: A fuzzy chance-constrained two-stage DEA approach

2021 ◽  
pp. 107879
Author(s):  
Mohammad Izadikhah ◽  
Majid Azadi ◽  
Mehdi Toloo ◽  
Farookh Khadeer Hussain
Keyword(s):  
Supply Chains ◽  
Public Transport ◽  
Two Stage ◽  
Dea Approach

Sustainable Supply Chains and International Soft Landings

2017 ◽  
pp. 232-247
Author(s):  
Ye-Sho Chen
Keyword(s):  
Public Health ◽  
Supply Chains ◽  
Positive Impact ◽  
Two Stage ◽  
Sustainable Supply Chains ◽  
Business Executives ◽  
Stage Process ◽  
Global Terrorism ◽  
Wetland Losses ◽  
Executives And Managers

Dealing with the “hidden dynamics” of diplomacy, espionage, and geopolitics has been a major challenge in international business. The rise of climate change and global terrorism, however, has brought nations together to seek for collaborative solutions. Coopetition is a strategy needed for business executives and managers engaging in strategic planning and operations of their international businesses in the 21st century. In this paper, we propose a two-stage process of coopetition consisting of sustainable supply chains and international soft landings. We illustrate how the two-stage process is used to develop a “Flying High, Landing Soft” platform of wetland entrepreneurship to address the growing global problem of wetland losses. The platform allows students to participate in exploring and developing businesses to maintain a healthy wetland and have positive impact on public health.

Investigating the impact of inventory inaccuracy on the bullwhip effect in RFID-enabled supply chains using colored petri nets

2019 ◽  
Vol 14 (2) ◽  
pp. 360-384 ◽  
Author(s):  
Maria Drakaki ◽  
Panagiotis Tzionas
Keyword(s):  
Supply Chain ◽  
Supply Chains ◽  
Petri Nets ◽  
Information Sharing ◽  
Bullwhip Effect ◽  
Colored Petri Nets ◽  
Content Type ◽  
Multi Stage ◽  
The Impact ◽  
Serial Supply Chains

PurposeInformation distortion results in demand variance amplification in upstream supply chain members, known as the bullwhip effect, and inventory inaccuracy in the inventory records. As inventory inaccuracy contributes to the bullwhip effect, the purpose of this paper is to investigate the impact of inventory inaccuracy on the bullwhip effect in radio-frequency identification (RFID)-enabled supply chains and, in this context, to evaluate supply chain performance because of the RFID technology.Design/methodology/approachA simulation modeling method based on hierarchical timed colored petri nets is presented to model inventory management in multi-stage serial supply chains subject to inventory inaccuracy for various traditional and information sharing configurations in the presence and absence of RFID. Validation of the method is done by comparing results obtained for the bullwhip effect with published literature results.FindingsThe bullwhip effect is increased in RFID-enabled multi-stage serial supply chains subject to inventory inaccuracy. The information sharing supply chain is more sensitive to the impact of inventory inaccuracy.Research limitations/implicationsInformation sharing involves collaboration in market demand and inventory inaccuracy, whereas RFID is implemented by all echelons. To obtain the full benefits of RFID adoption and collaboration, different collaboration strategies should be investigated.Originality/valueColored petri nets simulation modeling of the inventory management process is a novel approach to study supply chain dynamics. In the context of inventory errors, information on RFID impact on the dynamic behavior of multi-stage serial supply chains is provided.

A two-stage stochastic programming approach for identifying optimal postponement strategies in supply chains with uncertain demand

Omega ◽  
2019 ◽  
Vol 83 ◽  
pp. 123-138 ◽  
Author(s):  
Christoph Weskamp ◽  
Achim Koberstein ◽  
Frank Schwartz ◽  
Leena Suhl ◽  
Stefan Voß
Keyword(s):  
Stochastic Programming ◽  
Supply Chains ◽  
Uncertain Demand ◽  
Programming Approach ◽  
Two Stage ◽  
Postponement Strategies

Genetic Algorithm to Solve Multi-Period, Multi-Product, Bi-Echelon Supply Chain Network Design Problem

2009 ◽  
Vol 2 (4) ◽  
pp. 24-42 ◽  
Author(s):  
R. Dhanalakshmi ◽  
P. Parthiban ◽  
K. Ganesh ◽  
T. Arunkumar
Keyword(s):  
Supply Chain ◽  
Supply Chains ◽  
Raw Materials ◽  
Optimization Techniques ◽  
Network Design Problem ◽  
Production Plant ◽  
Two Stage ◽  
Cost Structures ◽  
Multi Stage ◽  
Product Costs

In many multi-stage manufacturing supply chains, transportation related costs are a significant portion of final product costs. It is often crucial for successful decision making approaches in multi-stage manufacturing supply chains to explicitly account for non-linear transportation costs. In this article, we have explored this problem by considering a Two-Stage Production-Transportation (TSPT). A two-stage supply chain that faces a deterministic stream of external demands for a single product is considered. A finite supply of raw materials, and finite production at stage one has been assumed. Items are manufactured at stage one and transported to stage two, where the storage capacity of the warehouses is limited. Packaging is completed at stage two (that is, value is added to each item, but no new items are created), and the finished goods inventories are stored which is used to meet the final demand of customers. During each period, the optimized production levels in stage one, as well as transportation levels between stage one and stage two and routing structure from the production plant to warehouses and then to customers, must be determined. The authors consider “different cost structures,” for both manufacturing and transportation. This TSPT model with capacity constraint at both stages is optimized using Genetic Algorithms (GA) and the results obtained are compared with the results of other optimization techniques of complete enumeration, LINDO, and CPLEX.

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