Value of Lead Time and Demand Information Sharing in Supply Chains

2013 ◽  
pp. 317-339
Author(s):  
Ali Mehrabi ◽  
Thierry Moyaux ◽  
Armand Baboli
Keyword(s):  
Supply Chains ◽  
Information Sharing ◽  
Lead Time ◽  
Demand Information

Supply Chain Competition with Information Sharing

2011 ◽  
Vol 486 ◽  
pp. 309-312
Author(s):  
Rong Yao He ◽  
Zhong Kai Xiong ◽  
Yu Xiong
Keyword(s):  
Supply Chain ◽  
Supply Chains ◽  
Information Sharing ◽  
Optimal Pricing ◽  
Market Demand ◽  
Pricing Policy ◽  
Supply Chain Competition ◽  
Demand Information ◽  
Total Profit

Given the case of two competing supply chains each consisting of one manufacturer and one retailer, we explore whether the retailers should share the market demand information they know with their manufacturers when the manufacturers do not know the same specific demand information. We also determine the optimal pricing policy and total profit for the retailers when each chain either shares or does not share market demand information. We find that sharing information is always more profitable for both retailer and supply chain.

Genetic Algorithm to Evaluate Downstream and Upstream Information Sharing

2020 ◽  
Vol 15 (1) ◽  
pp. 24-33
Author(s):  
Mansour Rached
Keyword(s):  
Genetic Algorithm ◽  
Supply Chain ◽  
Information Sharing ◽  
Decision Maker ◽  
Lead Time ◽  
Numerical Experiments ◽  
Optimal Allocation ◽  
Transportation Costs ◽  
System Cost ◽  
Demand Information

Background: In this paper, we present an approach to evaluate the information sharing in the supply chain. Materials and Methods: We propose a study of four scenarios of sharing upstream and downstream information simultaneously. Replenishment lead time is the upstream information studied in this work and demand information is the downstream one. We treat in this context the case of two-echelon (a warehouse and several retailers) and multi-products supply chain. Results: We focus our approach on the centralised decision, in which, the warehouse is the decision maker and his goal is to minimise the system cost independently. In our formulation, we consider a system cost composed of holding, ordering, penalty and transportation costs. Then, we use a Genetic Algorithm in order to approximate the optimal echelon inventory position at the warehouse and optimal allocation quantity of each item from the warehouse to the respective retailer, which minimises the system cost. Conclusion: Our approach is illustrated by some numerical experiments.

Information sharing in decentralised supply chains with partial collaboration

2021 ◽  
Author(s):  
Roberto Dominguez ◽  
Salvatore Cannella ◽  
Borja Ponte ◽  
Jose M. Framinan
Keyword(s):  
Supply Chains ◽  
Information Sharing
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