Determination of optimal ordering quantity and reduction of bullwhip effect in a multistage supply chain using genetic algorithm

Abstract

Allocating optimal ordering quantity and mitigation of bullwhip effect is one of the challenging parts in a modern multi echelon supply chain system. Genetic algorithm is used in this research to reduce the bullwhip effect and to determine optimal ordering quantity in a multistage supply chain consisting of six members. Real demand data of a manufacturing company has been used here to conduct the analyses. This research also pinpointed that genetic algorithm can be applied to reduce the cost of total supply chain. To calculate the total cost, five different costs with varying unit holding cost, in inventory cost is used for each of the members of supply chain. This paper also examines the importance of the limit set of the chromosomes of genetic algorithm and concluded that the lower range chromosomes provide a better result by reducing the total supply chain cost more than the range set in higher limit.Keywords: multistage supply chain; genetic algorithm; bullwhip effect; optimal ordering quantity; total supply chain cost; TSCC.Reference to this paper should be made as follows: Yesmin, T. and Hasin, M.A.A. (2012) 'Determination of optimal ordering quantity and reduction of bullwhip effect in a multistage supply chain using genetic algorithm', Int. J.

Optimization Algorithm in Supply Chain Management

“…In [52]bullwhip effect is such that a minute discrepancy in the demand from end consumers alters the whole flow of events as one proceeds higher level. Othman and Gomma [84] used control engineering and genetic algorithm to reduce bullwhip in supply chain and in [90]GA is applied for the same but to obtain the optimal amount of ordering in a chain with multiple stages. Tosun et al [88]used parallel GA approach and Devika et al [27]applied evolutionary multi-objective metaheuristics for the same.…”