Evolutionary game of information sharing on supply chain network based on memory genetic algorithm

Evolutionary game of information sharing on supply chain network based on memory genetic algorithm

Jian TanGuoqiang Jiang Zuogong Wang

Guiyang Institute for Big Data and Finance Guizhou University of Finance and Economics, Guiyang 550003, China

Economic School, Guizhou University of Finance and Economics, Guiyang 550003, China

Institute of Risk Management, Henan university Kaifeng 475004, China

Corresponding Author Email: 
| | | | Citation



The topological structure of supply chain network directly bears on the efficiency of information sharing, which is the key to the profit-making of enterprises. Taking supply chain network as a complex network, this paper analyses the evolutionary game of information sharing, and explores how network topology, probability of chromosome mutation and degree of punishment affect the evolutionary results of the network. Through the numerical simulation, it is found that a plateau exists in the information sharing process of a random network but does not exist in that of the regular network, indicating that the random network is more favourable to information sharing between enterprises of the supply chain; the probability of chromosome mutation is positively correlated with the frequency increase of information sharing but negatively with frequency stability; the degree of punishment contributes to the information sharing between the said enterprises. In long-term coopetition, the enterprises may play multiple games of information sharing and interest coordination, and tend to adjust their current game strategies based on the outcome of the previous game. In other words, the nodes in the supply chain network usually have memories. Considering this, the author introduced the genetic algorithm with memory to analyse the evolutionary game of information sharing in supply chain network. The resulting model boasts profound practical significance to the solution of information sharing and interests coordination among enterprises in supply chain network.


memory genetic algorithm, evolutionary game, supply chain network, information sharing

1. Introduction
2. Evolutionary game model
3. Memory genetic algorithm
4. Numerical simulation
5. Conclusion and expectation

This work was support by joint fund project of institute of international trade and economic cooperation, ministry of commerce (grant no.: 2016SWBZD06), soft science research project of Guizhou provincial science and technology department (grant no.: Guizhou kehe foundation [2016]1520_2).


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