Inventory control in supply chains: Alternative approaches to a two-stage lot-sizing problem

In the real world, applications with very large state and action spaces and unknown state transition probability, classical reinforcement learning algorithms usually show poor performance. One way to address the performance problem is to approximate the policy or value function. Fuzzy rule-based systems are amongst the well-known function approximators. This paper presents a Flexible Fuzzy Reinforcement Learning algorithm, in which value function is approximated by a fuzzy rule-based system. The proposed algorithm has a separate module for tuning the structure of fuzzy rules. Moreover, the parameters of the system are tuned during the learning phase. Next, the proposed algorithm is applied to the problem of inventory control in supply chains. In this problem, a fuzzy agent (supplier) should determine the amount of orders for each retailer based on their utility for supplier, by considering its limited supply capacity. Finally, a simulation is performed to show the capability of the proposed algorithm.

The overall operations of supply chain are affected by the increase of demand uncertainty. Inventory control is an important part in supply chain management. Under the requirement mentioned above, this paper studies the inventory control with uncertainty demand. Three-echelon inventory model of manufacture regarded as core enterprise is modeled, which assumes that uncertainty demand subjects to normal distribution. Redundancy inventory in the node enterprise of supply chain is discussed under the two inventory replenishment strategy (continuous review inventory and periodic review inventory). It 's shown that the result of this study is valuable to reduce the total cost of inventory and improve the performance of supply chain.

Inventory Control in Supply Chain: a Model-Free Approach*

The importance of reverse supply chain has been widely recognized in past two decades. Many companies use it in order to repair, replace, reuse and recycle their used products. On the other hand, due to independence of the decisions of the members in supply chain, the coordination mechanisms like contracts, can increase profit and improve decision making in supply chain, especially when information is asymmetric and each member has confidential information. In this paper, a three-echelon closed-loop supply chain including one manufacturer, one-third party and one retailer is developed. First, we survey Stackelberg games with sales-effort dependent demand and investigate supply chain performance under the centralized and decentralized scenarios. Next, three types of contract in supply chain including two parts tariff, cost-sharing and also revenue-cost sharing are analyzed and compared under asymmetric and symmetric information. We conclude that the supply chain can be coordinated under two parts tariff and revenue-cost sharing contracts when symmetric information exists, while supply chain coordination may not be achieved under asymmetric information. Finally, we proposed numerical examples and results show that revenue-cost sharing and two parts tariff have better performances.

Contributors

Cost-Effective Production and Inventory Control in Multi-echelon Supply Chains with Customer Prioritization

Distribution expansion planning in the presence of plug-in electric vehicle: A bilevel optimization approach

Contributors

Batu City is one of well known cities in East Java Province which is as center of tourism destination and also as center of apple production. There is growing small scale industry related to apple processed products, such as apple chips. In an effort to support the supply of raw materials and production planning, it is necessary to know the achievement of supply chain performance in a small industry of apples chips in Batu City. The method used is qualitative analysis to know the system of raw material inventory control and production planning system applied and analyze the performance of supply chain management, supply chain mapping with SCOR (Supply Chain Operations Reference) method, measurement of supply chain performance by using measured performance attribute that is Supply Chain Reliability, Supply Chain Responsiveness and Supply Chain Agility with performance metrics of Perfect Order Fulfillment (POF), Order Fulfillment Cycle Time (OFCT), Upside Supply Chain Flexibility, Upside Supply Chain Adaptability and Downside Supply Chain Adaptability. The results of this study indicate that the system of raw material inventory control and production planning system have been applied. Supply chain mapping, performance measurement of supply chain management need to be developed more to improve supply chain management performance in the small industry apple chips in Batu City.

Purpose: The purpose of this study is to compare the performance of two advanced supply chain coordination mechanisms, Vendor Managed Inventory (VMI) and Collaborative Planning Forecasting and Replenishment (CPFR), under a price-sensitive uncertain demand environment, and to make the optimal decisions on retail price and order quantity for both mechanisms. Design/ methodology/ approach: Analytical models are first applied to formulate a profit maximization problem; furthermore, by applying simulation optimization solution procedures, the optimal decisions and performance comparisons are accomplished. Findings: The results of the case study supported the widely held view that more advanced coordination mechanisms yield greater supply chain profit than less advanced ones. Information sharing does not only increase the supply chain profit, but also is required for the coordination mechanisms to achieve improved performance. Research limitations/implications: This study considers a single vendor and a single retailer in order to simplify the supply chain structure for modeling. Practical implications: Knowledge obtained from this study about the conditions appropriate for each specific coordination mechanism and the exact functions of coordination programs is critical to managerial decisions for industry practitioners who may apply the coordination mechanisms considered. Originality/value: This study includes the production cost in Economic Order Quantity (EOQ) equations and combines it with price-sensitive demand under stochastic settings while comparing VMI and CPFR supply chain mechanisms and maximizing the total profit. Although many studies have worked on information sharing within the supply chain, determining the performance measures when the demand is price-sensitive and stochastic was not reported by researchers in the past literature.

An integrated model for line planning and train scheduling based on the circulation of trains is proposed to reduce passenger dissatisfaction and operation costs for an urban rail transit line. The turnaround operations of trains and their departures from and arrivals at the depot were included in this model. Furthermore, binary variables were introduced to indicate whether train service existed, and a discrete event model was used to determine the order of the train services. In addition, a bi-level optimization approach is proposed to solve the integrated line-planning and train-scheduling problem, in which the number of required train services, the headways between train services, the departure times, and the arrival times were optimized simultaneously on the basis of passenger demand. The performance of the proposed integrated model and bi-level approach is illustrated with a case study of the Beijing Yizhuang line.

A supply chain coordination mechanism with suppliers’ effort performance level and fairness concern

Against the backdrop of cap-and-trade regulations, we construct a low-carbon supply chain in which a seller holds the manufacturer’s equity. We investigate the impact of the seller’s equity holding and the cap-and-trade regulations on the supply chain members’ optimal decisions, profits and coordination in the cases of information symmetry and asymmetry. We find that, regardless of whether there is information asymmetry or symmetry, the manufacturer always benefits from an equity holding, while the seller can only earn higher profits through equity holding if the percentage of equity holding and the level of consumer low-carbon awareness are both sufficiently high. Both the seller and the manufacturer prefer the information asymmetry scenario when the manufacturer’s efficiency in emission reduction is below a particular threshold. In addition, equity holding can incentivize the manufacturer to share its information with the seller. Equity holding is beneficial for emission reduction and market demand but is not always beneficial for improving the supply chain’s total profit and reducing the supply chain’s total carbon emissions. Finally, with a transfer payment contract, a decentralized supply chain can obtain the same optimal profits as in the centralized supply chain scenario, and both the manufacturer and seller can earn higher profits than before.

This work investigates an unmanned aerial vehicle (UAV) assisted IoT system, where a UAV flies to each foothold to collect data from IoT devices, and then return to its start point. For such a system, we aim to minimize the energy consumption by jointly optimizing the deployment and flight trajectory of UAV. It is a mixed-integer non-convex and NP-hard problem. In order to address it, a bilevel optimization approach is proposed, where an upper-level method aims to optimize the deployment of UAV and a lower-level one aims to plan UAV flight trajectory. Specifically, the former optimizes the number and locations of footholds of UAV. This work proposes an improved dandelion algorithm with a novel encoding strategy, in which each dandelion represents a foothold of UAV and the entire dandelion population is seen as an entire deployment. Then, two mutation strategies are designed to adjust the number and locations of footholds. Based on the footholds of the UAV provided by the former, the latter transforms flight trajectory planning into a traveling salesman problem (TSP). This work proposes an iterated greedy algorithm to solve it efficiently. The effectiveness of the proposed bilevel optimization approach is verified on ten instances, and the experimental results show that it significantly outperforms other benchmark approaches.

As supply chains become bigger and dynamically structured involving multiple organizations with different interests, it is impossible for a single organization to control a whole supply chain. So, decentralization of decision rights is an inevitable facet of managing modern supply chains. However, controlling in a decentralized mode can fail without appropriate coordination mechanisms. When the agents of a supply chain are not willing to cooperate in terms of information sharing, the whole supply chain can exhibit expensive inefficiencies such as the bullwhip effect. In this paper, we design a trustworthy decentralized coordination mechanism for dynamic lot-sizing in distribution networks, as an effort to motivate information sharing. We design multiple auctions and each auction coordinates the plans of a supplier and its customers by trading the right of managing the supplier's inventory plan. The coordination mechanism makes a reasonable profit and the profit is divided in an agreeable way. Also, the profits are actual because of the capability of supporting a truth-telling environment. Therefore, the designed coordination mechanism is trustworthy in that it guarantees the right benefits to all the agents in return for information sharing.