Search

Highlights • Jointly optimizes procurement, production and shipping decisions for a two-stage closed-loop supply chain system. • Presents two mathematical models for two different raw material (RM) replenishment strategies. • Proposes an efficient iterative search algorithm that guarantees convergence to near optimal solutions. • The Incorporation of RM replenishment strategy greatly impacts production sequencing, lot sizing and shipping decisions. Abstract This paper seeks to jointly optimize the raw material (RM) procurement and shipping decisions as well as those pertaining to the lot sizing and the production sequencing of manufactured and remanufactured products for a centralized two stage closed loop supply chain, wherein the vendor and the buyer operate under consignment stock partnership. Most of the existing closed loop models have overlooked the tradeoffs involved in optimizing RM replenishment strategy in conjunction with the production sequence, and assumed the predetermined sequence of (R, P) where R remanufactured batches are produced first followed by P manufactured batches as this sequence prioritizes the clearance of the accumulated inventory of returned items. As such, we jointly optimize the aforementioned interrelated decisions, alongside others as well, under two RM replenishment strategies; multi-to-one (MTO) and one-to-multi (OTM) where a mathematical model is developed for each strategy. In essence, this work seeks to assess what impact would the incorporation of RM procurement decisions have on the shipping and production policy downstream. Extensive computational experiments, carried out under different settings of the problem parameters, indicate that accounting for RM procurement strategy greatly impacts not only the production sequence, but extends to include the lot sizing and shipping decisions as well. Furthermore, the computational study suggests that it is economically advantageous to synchronize RM orders such that they take place right at the time needed for the production of newly manufactured products. [ABSTRACT FROM AUTHOR]

In most deterministic and stochastic inventory models encountered in the literature, the optimal policy is determined on the basis of the assumption that lead-time is a given parameter. However, lead-time is composed of several controllable components such as run time, setup time, waiting time, moving time, and lot size inspection time. In this paper, we study a stochastic inventory continuous review system with lead-time depending on lot size and setup time. We assume that the lead-time can be expressed as the product of productive time and a given non-productive factor that reflects the portion of the lead-time such as waiting and moving times. For general demand distributions, the resulting mathematical model is too complex to be solved analytically. For such distributions, we developed an Awesim simulation model for the continuous review system with lot size and lead-time interaction. This simulation model is interfaced with an optimization procedure based on a proposed partial enumeration method to search for the least-cost lot size and reorder point. [ABSTRACT FROM AUTHOR]