Using simulation-based system dynamics and genetic algorithms to reduce the cash flow bullwhip in the supply chain

被引:38
作者
Badakhshan, Ehsan [1 ]
Humphreys, Paul [1 ]
Maguire, Liam [2 ]
McIvor, Ronan [1 ]
机构
[1] Ulster Univ, Ulster Business Sch, Derry, North Ireland
[2] Ulster Univ, Fac Comp Engn & Built Environm, Jordanstown, North Ireland
关键词
supply chain management; artificial intelligence; simulation; genetic algorithms and the bullwhip effect; NETWORK DESIGN; OPTIMIZATION; IMPACT; SUSTAINABILITY; VARIABILITY; RESILIENCE; COST; RISK;
D O I
10.1080/00207543.2020.1715505
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The bullwhip effect (BWE) is a phenomenon, which is caused by ineffective inventory decisions made by supply chain members. In addition to known inefficiencies caused by the bullwhip effect within a supply chain product flow, such as excessive inventory, it can also lead to inefficiencies in cash flow such as the cash flow bullwhip (CFB). The CFB reduces the efficiency of the supply chain (SC) through heterogeneous distribution of cash among supply chain members. This paper aims to decrease both the BWE and the CFB across a SC through applying a simulation-based optimisation approach, which integrates system dynamics (SD) simulation and genetic algorithms. For this purpose, cash flow modelling is incorporated into the SD structure of the beer distribution game (BG) to develop the CFB function. A multi objective optimisation model is then integrated with the SD-BG simulation model. Finally, a genetic algorithm (GA) is applied to determine the optimal values for the inventory, supply line, and financial decision parameters. Results show that the proposed integrated framework leads to efficient liquidity management in the SC in addition to cost management.
引用
收藏
页码:5253 / 5279
页数:27
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