Optimal and heuristic base-stock levels and review periods in a serial Supply Chain

Abstract

A key issue in a Supply Chain (SC) concerns the control policy to determine the optimal order-up-to levels or base-stock levels and review periods. In this study, a mathematical model is developed to determine the optimal installation or local base-stock levels and review periods for every member in the SC that uses periodic-review order-up-to (S) policy, with the consideration of the ordering cost at every installation. Our model considers four members, namely, a supplier, a manufacturer, a distributor and a retailer. We obtain optimal review periods and base-stock levels (in the class of order-up-to policy) for different SC settings. In addition, two Genetic Algorithms (GAs) have been developed to determine the best base-stock levels and review periods for all members in the SC.

Inventory parameters for a serial supply chain with lost sales through genetic algorithm approach

“…The present authors have considered the SC settings and cost setting considered by Sethupathi and Rajendran (2010) except for retailer lost sales cost which is doubled with their shortage cost considered for retailer. This is purposefully done to give high penalty for lost sales.…”

“…The authors considered crossover rate CoR as 1.0 in this study and generated as many offspring's as the number of parent chromosomes. The MGGA makes use of the crossover operator, called the gene-wise crossover operator (Daniel and Rajendran, 2006;Sethupathi and Rajendran, 2010) that makes use of the information of genes of all the chromosomes that are present in p_pn and builds an offspring out of those chromosomes. The modified gene-wise crossover operator is explained with the following example in Figure 4.…”

“…According to Shang and Song (2003) and Daniel and Rajendran (2006), the calculation of base stock levels for each stage in a SC and for minimising the total SC cost by considering inventory holding cost and shortage cost are cumbersome and computationally complex. Sethupathi and Rajendran (2010) considered a serial SC and have developed a model based on base stock policy with backlog. Further, they devised GA procedures to find out best base stock levels and ordering periods for members in the SC.…”

A serial inventory system with supplier selection and order quantity allocation considering transportation costs

“…Daniel and Rajendran (2005) considered a singleproduct serial supply chain operating with a base-stock policy and addressed the problem of optimizing the inventory levels using a genetic algorithm. Some researchers used simulation methodologies to develop and evaluate inventory policies in serial supply chain systems: Lee and Billington (1993), Glasserman and Tayur (1995), Axsater (2003), and Sethupathi and Rajendran (2010). These studies have not considered freight rates or supplier selection aspects in their models.…”