Multi-objective optimisation framework of genetic programming for investigation of bullwhip effect and net stock amplification for three-stage supply chain systems Online publication date: Tue, 12-Jan-2021
by Akhil Garg; Surinder Singh; Liang Gao; Xu Meijuan; Chee Pin Tan
International Journal of Bio-Inspired Computation (IJBIC), Vol. 16, No. 4, 2020
Abstract: In this work a multi-objective optimisation framework of genetic programming (GP) in the modelling of bullwhip effect and NSA for centralised and decentralised supply chain systems has been proposed. The individual and interactive effect of these four input factors has been investigated on bullwhip effect and NSA by adapting the parametric and sensitivity approach on the formulated models. The appropriate settings of dominant input factors (batch ordering and demand signal processing for a decentralised chain, demand signal processing and rationing shortage gaming for a centralised chain) are suggested to optimise the bullwhip effect and NSA of three-stage supply chain simultaneously. The implications and advantages of proposed optimisation framework will be useful for business practitioners to monitor and supervise the sudden demand amplification that generally faced by them in the supply chains.
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