Stochastic Dynamic Demand Inventory Models with Explicit Transportation Costs and Decisions

Recent supply chain literature and practice recognize that significant cost savings can be achieved by coordinating inventory and transportation decisions. Although the existing literature on analytical models for these decisions is very broad, there are still some challenging issues. In particular, the uncertainty of demand in a dynamic system and the structure of various practical transportation cost functions remain unexplored in detail. Taking these motivations into account, this dissertation focuses on the analytical investigation of the impact of transportation-related costs and practices on inventory decisions, as well as the integrated inventory and transportation decisions, under stochastic dynamic demand. Considering complicated, yet realistic, transportation-related costs and practices, we develop and solve three classes of models: (1) Pure inbound inventory model impacted by transportation cost; (2) Pure outbound transportation models concerning shipment consolidation strategy; (3) Integrated inbound inventory and outbound transportation models. In broad terms, we investigate the modeling framework of vendor-customer systems for integrated inventory and transportation decisions, and we identify the optimal inbound and outbound policies for stochastic dynamic supply chain systems. This dissertation contributes to the previous literature by exploring the impact of realistic transportation costs and practices on stochastic dynamic supply chain systems while identifying the structural properties of the corresponding optimal inventory and/or transportation policies. Placing an emphasis on the cases of stochastic demand and dynamic planning, this research has roots in applied probability, optimal control, and stochastic dynamic programming

The transporter's impact on channel coordination and contractual agreements

This dissertation focuses on the recent supply chain initiatives, such as Vendor Managed Inventory (VMI) and Third-Party Logistics (3PL), enabling the coordination of supply chain entities; e.g., suppliers, buyers, and transporters. With these initiatives, substantial savings are realizable by carefully coordinating inventory, transportation, and pricing decisions. The impact is particularly tangible when the transporter's role and the transportation costs are explicitly incorporated into decision mechanisms that aim to coordinate the supply channel. Furthermore, expanding the perspective of channel coordination by introducing the transporter as an individual party in the channel provides tangible benefits for each member of the channel. Recognizing the need for further analytical research in the field of multi-echelon inventory and channel coordination, we developed and solved a class of integrated inventory and transportation models with explicit shipment consolidation considerations. Moreover, we examined transporter-buyer and supplier-transporter-buyer channels and solved centralized and decentralized models for these channels with the aim of investigating the impact of transporters on channel performance. In this dissertation, we also developed efficient coordination mechanisms between the transporter and the other parties in the channel

Shipment consolidation and distribution models in the international supply chain

With the increasing competition in global trade, buying and transporting items effectively in the international network are critical and challenging problems for many companies. The objective of this study is to design a cost-effective consolidation and distribution method to transport shipments in a global network. In the dissertation, we investigate an integrated consolidation problem in the international supply chain, where a US manufacturing company buys multiple items from China. A proactive order consolidation strategy is proposed. Different from current practices, our approach consolidates items in China considering inland transportation in US. This strategy is modeled to minimize the total costs by effectively loading items into an ocean container considering subsequent inland transportation cost and handling cost given container capacity and packing constraints. Two difficult combinatorial optimization problems, such as a mode selection problem and a three-dimensional bin packing problem, are combined into the model. Due to the problem complexity, approximation algorithms are proposed to solve the model. The basic model is extended to consider the inland multi-stop delivery and multi-period planning horizon. Several solution methodologies are developed and evaluated to solve large-scale problems. Based on the numerical results, it is observed that our proposed methods could achieve up to 30% cost savings compared with the current shipping practices. The algorithms we developed could obtain the good implementable solution in a reasonable time for real-world problems

A collaborative framework in outbound logistics for the us automakers

The competitive landscape of the U.S. automotive market has transformed from the traditional Big Three players to too many viable players. In 2008-2009, the harsh market conditions, excess production capacity, capital asset redundancies, and many inefficient strategies submerged as the roadblocks for the US automakers to stay competitive and profitable in the North American market. In this new competitive era, cross-company collaboration in product development, standardizing and communizing supply base, sharing flexible manufacturing platforms, using common inbound and out bound logistics service providers and warehousing etc. can play vital roles for the US automakers to reduce overall cost and return to profitability. Through the horizontal collaboration in the outbound logistics operations, these companies can create close-knit business partnership and act faster than the foreign rivals in delivering finished vehicles at the optimum cost. The optimization of outbound logistics operations through consolidation and collaboration among OEMs has tremendous potential to contribute to the profitability by lowering the cost of transportation, in-house inventory, transportation time, and facility costs. The collaboration in the intra- and inter-OEM outbound logistics operations is a critical area that the US automakers need to pay attention and prioritize in their cost reduction initiatives. This research presents an integrated collaboration framework for the outbound logistics operations of the US automakers. In our framework, we propose three potential levels for the US automakers to form outbound logistics collaboration: operational, tactical, and strategic. Our research proposition is to improve the performance of outbound logistics systems of automotive OEMs by means of horizontal collaboration between plants and competing OEMs. The proposed research thus relates to the literature on logistics system design and management and horizontal collaboration in supply chain management. The collaboration framework is demonstrated through a real world case study in US automotive industry. The contribution of this research is the introduction of a framework for intra- and inter-OEM collaboration and the development of novel logistics network design and flow models integrated with inventory models, lost sales, and expedited shipment. Besides the contribution to the academic literature, the proposed collaborative distribution system is a new concept in the automotive industry. Hence, this novel research work will also benefit to the practitioners. Keywords: Operational Collaboration, Tactical Collaboration, Strategic Collaboration, Frequency based Inventory, Customer Patience and Lost Sales, Expedited Shipments

Multi-echelon Inventory Control with Integrated Shipment Decisions

Rising fuel prices and increasing environmental awareness emphasizes the importance of the transportation aspect in logistics. This calls for new improved inventory control methods that consider the effects of shipment strategies in a more realistic manner. This thesis, consisting of an introduction and three scientific papers, studies how shipment decisions can be included in the inventory control of distribution systems. The systems studied in the papers consist of a central warehouse that supplies goods to a number of retailers that face stochastic customer demand. The first two papers consider a system where shipments from the central warehouse are consolidated to groups of retailers periodically. This means that replenishment orders of one or several items from different retailers are consolidated and dispatched at certain time intervals. By doing so, transportation cost savings can be realized and emissions can be reduced. This is achieved by filling the vehicles or load carriers to a higher extent and by using cheaper and more environmentally friendly, transportation modes. The first paper explicitly focuses on how to include more realistic transportation costs and emissions. This is done by obtaining the distribution of the size of an arbitrary shipment leaving the central warehouse (directly affected by the shipment frequency). It is thereby easy to evaluate any system where the transportation costs and emissions are dependent on the size of the shipment. The paper also provides a detailed analysis of a system where there is an opportunity to reserve shipment capacity on an intermodal truck-train-truck solution to at least one of the retailer groups. For this system it is shown how to jointly optimize the shipment intervals, the reserved capacities on the intermodal transportation modes and the reorder points in the system. The presented optimization procedure is applicable in three scenarios; (i) the emissions are not considered, (ii) there is a fixed cost per unit of emission, and (iii) there is a constraint on the maximum emissions per time unit. The second paper extends the analysis of a similar time-based shipment consolidation system to handle compound Poisson demand (instead of pure Poisson demand). This system has a simpler transportation cost structure, but the more general demand structure makes the model applicable for a broader array of products. The paper also extends the model to handle fill rate constraints, which further improves the practical applicability. The cost analysis is performed with a new methodology, based on the nominal inventory position. This variable is a helpful tool for analyzing the dynamics of distribution systems. Another system where this tool can be used is studied in the third paper. In this paper all stock points use installation stock (R,Q) ordering policies (batch ordering). This implies that situations can occur when only part of a requested retailer order is available at the central warehouse. The existing literature predominantly assumes that the available units are shipped immediately and the remaining units are shipped as soon as they arrive to the central warehouse, referred to as partial delivery. An alternative is to wait until the entire order is available before dispatching, referred to as complete delivery. The paper introduces a cost for splitting the order and evaluates three delivery policies; the PD policy (only partial deliveries are used), the CD policy (only complete deliveries are used), and the state-dependent MSD policy (an optimization between a partial and a complete delivery is performed for each delivery). The MSD policy is proven to perform better than both the PD and the CD policy. In a numerical study it is shown that significant savings can be made by using the MSD policy