In this paper, a manufacturing system is considered with stochastic item failure, replacement and order lead times of statistically identical items.
Recently, Heydari and Norouzinasab (2016) proposed an inventory model for incentive policy to coordinate ordering, lead time, and pricing strategies in a two-echelon manufacturing supply chain.
The study has demonstrated that logistics and packing postponement strategies can improve the performance of logistics (total inventory and order lead-time) and, at the same time contribute to reducing the environmental impact of CO2 emissions from transportation process.
This has a positive impact on the ordering lead-time, human processing time, the inventory levels and number of stock-outs.
A mathematical model is employed in this study for optimizing the order quantity, lead time, ordering cost and number of deliveries in one production cycle.
Numerical examples are provided to illustrate the models and sensitivity analysis has been carried out to analyze the behavior of the key parameters on order quantity, lead time, ordering cost, number of deliveries from the vendor to the buyer in one production run and the integrated total cost of the proposed models.
Further, based on the convexity behaviour of the objective function with respect to the decision variable, the following linear function case algorithm is designed to find the optimal values for order quantity, lead time, ordering cost and the number of deliveries in one production cycle.
The solution procedure is to determine the optimal solutions of order quantity, ordering cost, lead time and the number of deliveries from the single vendor and the single buyer in one production run, so that the integrated total cost incurred has the minimum value.
Further, based on the convexity behaviour of the objective function with respect to the decision variable, the following logarithmic function case algorithm is designed to find the optimal values for order quantity, lead time, and the number of deliveries in one production cycle.
Heydari and Norouzinasab (2016) have developed coordination of pricing, ordering and lead time decisions in a manufacturing supply chain.
