Supply chain uncertainties pose a massive and ever-present challenge for modern companies. These can manifest in two contrasting scenarios: supply surplus, where companies have excess items, shortages, there is an insufficient quantity of goods. Each situation demands different approach from businesses to adapt the varying outcomes maintain competitive edge market. Product backordering one impo...

In this paper, an inventory model for two-stage supply chain is investigated. A supply chain with single vendor and single buyer is considered. We assume that shortage as a backorder is allowed for the buyer and the vendor makes the production set up every time the buyer places an order and supplies on a lot for lot basis. With these assumptions, the joint economic lot size model is introduced ...

We study a single-product periodic-review inventory model in which the ordering quantity is either zero or at least a minimum order size+ The ordering cost is a linear function of the ordering quantity, and the demand in different time periods are independent random variables+ The objective is to characterize the inventory policies that minimize the total discounted ordering, holding, and backo...

We study a manufacturing firm that builds a product to stock to meet a random demand. Production time is deterministic, so that if there is a backlog, customers are quoted a firm lead time that is proportional to the backlog. In order to represent the customers’ response to waiting, we introduce a new defection function — the probability that a customer chooses not to order as a function of the...

We consider a single-item make-to-stock production system. The item is demanded by several classes of customers arriving according to Poisson processes with different backorder costs. Item processing times have an Erlang distribution. This allows us model the information on the production status in a tractable way and to investigate the impact of processing time variability. Using a Markov Deci...

Inventory policies for joint remanufacturing and manufacturing have recently received much attention. Most efforts, though, were related to (optimal) policy structures and numerical optimization, rather than closed form expressions for calculating near optimal policy parameters. The focus of this paper is on the latter. We analyze an inventory system with unit product returns and demands where ...

With the advancement of technologies, industries tries to adopt advantages technology. Customers are busy in their daily life, and online platform is best option for retail, whereas traditional customers still prefer visit retail shop. Few choose product but buy it offline or vice-versa . Owing all those circumstances, current study focuses on an intelligent dual channel (online-to-offline) str...

This study presents a novel approach to mixed-integer linear programming (MILP) model for periodic inventory management that combines reinforcement learning algorithms. The rolling horizon method (RHM) is multi-period optimization applied handle new information in updated markets. RHM faces limitation easily determining prediction horizon; overcome this, dynamic developed which RL algorithms op...