Sharif Digital Repository

The integrative supply chain management is one of the main business processes between final consumer and supplier and it is formed by responsibilities such as production, services and information those have added value for customers and beneficiaries. Therefore and as the goal of a chain is maximization of gained value for the factors involved in chain, so, this goal can be more accessible by decreasing transportation (transportation method, tracking, …) and stock costs (conservation, ordering, …). As its purpose, this thesis intends to introduce and increase the options of goods transportation possibilities between retailers’ warehouses and evaluation of its effect on transportation and... 

Nowadays, due to various reasons awareness of environment preservation has increased throughout the supply chain. So supply chain owners revise their carbon footprint. Among different methods of reducing, operational decisions (e.g. ordering quantity or transportation method) has less cost and time for observing outcomes. Our main focus is on inventory models that taking account environment considerations especially carbon emissions. Through these models, vendor-managed inventory model for reducing total cost of chain gets more attention than past. The purpose of this work is to develop a two echelon supply chain with multi-item for replacing inventory. This model includes warehouse capacity... 

Although inventory control under discrete demand in dynamic quantities and time intervals are very common in reality, existing literature has largely ignored them. In this thesis, we investigate the inventory control decisions in a two echelon supply chain. The vendor supplies a product to several retailers, buying discrete quantities in pre-determined time intervals. The order quantity and order cycles for each retailer can be different from others. We have developed a new efficient algorithm to find the optimal ordering policy involves the scheduling and the order quantity of vendor to his supplier to minimize his cost function in infinite time horizon. Moreover, we have designed a revenue... 

This study proposes a deep reinforcement learning approach to solve a perishable inventory allocation problem in a two-echelon supply chain. The inventory allocation problem is studied considering the stochastic nature of demand and supply. The examined supply chain includes two retailers and one distribution center (DC) under a vendor-managed inventory (VMI) system. This research aims to minimize the wastages and shortages occurring at the retailer's sites in the examined supply chain. With regard to continuous action space in the considered inventory allocation problem, the Advantage Actor-Critic algorithm is implemented to solve the problem. Numerical experiments are implemented on...