Thesis: M. Eng. in Supply Chain Management, Massachusetts Institute of Technology, Supply Chain Management Program, 2018. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 36-38). / In today's world, the e-commerce market is growing rapidly and becoming more competitive. While many players in the industry are attempting to get their share of pie, consumers are demanding faster deliveries and free shipping. This market growth and change in consumer behavior provides an exciting opportunity for companies to compete. In order to meet the new consumer demand, companies need to find better ways to deliver faster. Faster delivery times can be achieved by using an optimization model to plan delivery network and operations. Typically, this optimization model has been based on minimizing cost. However, in the current market, lowest cost is not necessarily the best driver of sales as the consumer culture enters an era of instant gratification. We argue that minimizing customer waiting time will bring better performance and win over market share by providing the quickest delivery service that is expected by the majority of consumers. We propose solving the location routing problem (LRP) aiming at minimizing customer waiting time with capacitated depots and vehicles. We take two approaches to solve this problem: mathematical model and heuristic algorithm. The mathematical model obtains the optimal solution, but it has a limitation on the size of the problem due to the NP-hardness of the LRP. Therefore, we introduce three different variations of Simulated Annealing (SA) algorithm to solve the Capacitated Latency Location Routing Problem (CLLRP). According to the comparison results on a popular benchmark test, one of the designed SAs, the Iterative Simulated Annealing algorithm, consistently provides the best combination of performance and computation time compared to the other two SAs. Therefore, this specific algorithm is further compared to the mathematical model on some problem instances. The comparison results demonstrate that the proposed algorithm performs competitively with the algorithms in the literature and the mathematical model. / by Eugene Sohn. / M. Eng. in Supply Chain Management

Thesis: M. Eng. in Supply Chain Management, Massachusetts Institute of Technology, Supply Chain Management Program, 2017. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 46-47). / Drug counterfeiting is one of the major issues in the pharmaceutical industry across the world. These products could cause damages from ineffective treatments to death of patients. In order to fight against counterfeit drugs, the US government introduced Drug Supply Chain Security Act (DSCSA) mandating that all prescription drugs should be serialized. In addition, it mandates all pharmaceutical companies in the U.S. to provide tracking documents in response to a tracing request from FDA. While the act aims to improve drug security across the pharmaceutical industry, it poses a huge impact across the supply chain on both physical flow and information flow. This research evaluates the supply chain impact at an industry level. In this thesis, we evaluate the supply chain impact of Matryoshka model and Unit level model supported by a decentralized information flow. The thesis then evaluates the supply chain impact from three aspects, operational cost, IT infrastructure cost and capital investment. We reference Nabiyeva and Wu's research on centralized information flow model to conduct an exhaustive supply chain impact evaluation across the centralized model and the decentralized model. We conclude that among all these scenarios, unit level model under centralized information flow design bears the highest cost as it requires higher IT investment. On the other hand, the matryoshka model under decentralized information flow has a least supply chain impact from the cost perspective with low IT investment. / by Meng Ying Chang and Raghavendran Mohan. / M. Eng. in Supply Chain Management

Thesis: M. Eng. in Supply Chain Management, Massachusetts Institute of Technology, Supply Chain Management Program, 2017. / Cataloged from PDF version of thesis. / Pharmaceutical supply chains are strictly regulated and work within unique constraints. Traditionally, innovator companies that are manufacturing the product have no direct interaction with the end users (treatment sites or individual patients); rather, over 90% of the orders go through intermediary wholesalers and distributors. However, with the introduction of new technologies for patients to manage their own health, federal regulations coming into effect on supplier responsibility for tracking drugs down to the user, and ever more pressure to cut costs and justify the high cost of medicine, manufacturers are actively reshaping their role in the pharmaceutical supply chain. Our objective in this thesis project was to support our Sponsor Company, a "Big Pharma" company with a wide range of medicines, to understand the key cost drivers of their current distribution channel and to explore the impact that a shift to an alternative distribution channel would have from a financial and operational standpoint. We first conducted a literature review to examine the existing research on costing methodologies, the impact of home delivery for clinical care and the drug distribution landscape. The literature shows some evidence that home delivery improves patient adherence and reduces inventory costs for suppliers. We then analyzed a targeted product's distribution network within the US by building a cost-to-serve model, which maps out the end-to-end service components conducted by the Sponsor Company. With this model we were able to test the supply chain impacts of volume change and a gradual shift to alternative distribution channels. The results of the model showed that for this particular product, working capital was a key cost driver, shifting volume to incorporate alternative distribution channels is highly beneficial; even some significant increases in operating costs are effectively neutralized by reductions in working capital for the entire channel. Aside from the model results, we recommend validating the assumptions and suggest that this 'bottom-up' costing model be extended for other products and geographies and used to inform the company's overall corporate strategic planning exercise. The cost-to-serve model framework can also be extended beyond the pharmaceutical industry to benefit consumer facing industries considering an omni-channel strategy. / by Qi Zhang and Muching Zhang. / M. Eng. in Supply Chain Management

Thesis: M. Eng. in Supply Chain Management, Massachusetts Institute of Technology, Supply Chain Management Program, 2017. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 46-49). / Many businesses struggle to optimize the flow of inventory and finished goods through existing plants and facilities. The integration of inventory costs, organizational processes, and changing business dynamics make it difficult to determine the optimal flow. This thesis examines the flow of raw materials and finished goods through the supply chain of a multi-national oilfield services company. We study a centralized inventory approach, assessed through heuristics, against the existing decentralized approach. Sensitivity analysis with regard to service level, and mode of transport strengthened the analysis. We show that demand aggregation and lead time are important factors in determining the upper echelon for a company's internal distribution model. Potential safety stock reduction is 2%, which is mainly due to the improved coordination for materials flowing to the final echelon in the supply chain. However, pipeline inventory increases by 12% as a result of longer lead times. / by Patrick Scott and Boxi Xu. / M. Eng. in Supply Chain Management

Thesis: M. Eng. in Supply Chain Management, Massachusetts Institute of Technology, Supply Chain Management Program, 2018. / Cataloged from PDF version of thesis. "June 2018." / Includes bibliographical references (pages 79-80). / A set of contracts guides every movement of cargo from one point to another. In this thesis, we focus on the contract between the charterer and the ship-owner in the liquid bulk ocean-shipping market. The contracting process begins with the two parties finding each other suitable and ends with one party being compensated in compliance with the terms and conditions of the contract for meeting a set of considerations. The question we answer is how emerging technologies, primarily Blockchain, can be used to make this process more efficient in terms of time and cost. Our research shows that while there are a considerable cost and time savings possible for certain aspects of the contracting process, there are some problem areas, such as the negotiations, that cannot be solved with the help of existing technology. We also conclude that the proposed solution needs to offer an end-to-end contract and document management tool rather than just being an improvement for one particular step in the process. An industry-wide consortium led Blockchain-based solution has potential to find wide acceptability and impact in terms of increased efficiency. / by Harshvardhan. / M. Eng. in Supply Chain Management

Thesis: M. Eng. in Supply Chain Management, Massachusetts Institute of Technology, Supply Chain Management Program, 2017. / Cataloged from PDF version of thesis. / Includes bibliographical references (page 58). / Due to the long lead times and complexity in drug development and approval processes, pharmaceutical companies use long range planning to plan their production for the next 10 years. Capacity planning is largely driven by the long-term demand and its forecast uncertainty. The impact of uncertainties at manufacturing level, such as factory productivity and production success rate, are not entirely taken into account since only the average values of each manufacturing parameter are used. Can we better allocate production among manufacturing facilities when both demand and manufacturing uncertainties are considered? In this thesis a stochastic optimization approach is followed to minimize the deviation from target capacity limit under different manufacturing and demand scenarios. The mixed integer linear model incorporates the impact of demand and manufacturing variation on production allocation among manufacturing facilities through Monte Carlo generated scenarios. The thesis model is designed in a way that can be used as a decision tool to perform robust capacity planning at the strategic level. / by Sifo Luo. / M. Eng. in Supply Chain Management

Thesis: M. Eng. in Supply Chain Management, Massachusetts Institute of Technology, Supply Chain Management Program, 2019 / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 66-70). / With the increased application of cognitive computing across the spectrum of industries, companies strive to ready their people and machines for future system change. Based on resource constraints, business needs, and the speed of change, many companies may opt for system augmentation rather than the adoption of entirely new systems. At the same time, changes in technology are increasing at paces never before realized. Against this backdrop, human actors and machines are working together interactively in new and increasing ways. Further, recent business model innovations, particularly in the retail space, have cast focus on logistics execution as a potential major competitive advantage. In this context, we considered the conceptual question of how best to iteratively improve a logistics planning system, which is composed of both human and machine actors, to reduce transportation and labor costs and increase the ability of the organization to think and act strategically. / In order to front these current technological realities - the need to stage for agent based systems and cognitive computing, the likelihood of system retrofit over rebuild, the ever increasing rate of change, and the rapid intertwining of human and machine roles - we proposed using human-machine interaction (HMI) design paradigms to retrofit an existing loosely coupled human-machine planning system. While HMI principles are normally applied to tightly coupled systems such as jet airplanes, the HMI architectural design applied novelly in this case showed significant application to an existing loosely coupled planning system. In addition to meeting the realities of today's competitive landscape, the developed HMI framework is tailored to a retrofit situation and also meets resiliency considerations. That novel conceptual proposal of HMI frameworks to an existing loosely coupled joint cognitive planning system shows tremendous promise to address these imminent realities. / With regards to the particular freight planning system considered, 71% of manual interventions were caused by the wrong sourcing facility being assigned to supply pallets to a customer. The remaining intervention causes were carrier changes 18%, customer restrictions 9%, and one change prompted by a data discrepancy. Further, at a conceptual level, the application of HMI frameworks to an existing freight planning system was effective at isolating data and alignment incongruences, displayed lower communication costs than recurrent system rework processes, and tethered well with system resiliency factors. / by John Bishop Ravenel. / M. Eng. in Supply Chain Management / M.Eng.inSupplyChainManagement Massachusetts Institute of Technology, Supply Chain Management Program

Thesis: M. Eng. in Supply Chain Management, Massachusetts Institute of Technology, Supply Chain Management Program, 2019 / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 52-53). / While festivals bring a reason to cheer for everyone, businesses dealing with a spike in demand for perishables may have to live with the misery of lost sales and/or expired items. In the case of the dairy industry that deals with liquid milk, both raw material, and finished goods are perishable, which implies that merely stockpiling inventory of either item, without paying attention to potential inventory losses, cannot be an optimal strategy. In developing countries, the supplier base for perishables like milk, fruits, vegetables, flowers, etc. mostly comprise of small farmers instead of corporate/professional agencies, thus leading to supply variability. During special occasions like festivals, as individuals set aside more of the raw material for their own consumption, we encounter a reduction in supply. Around the same time, we notice a spike in customer demand, leading to a demand-supply mismatch. Companies dealing with perishables need an analytical approach to manage this. / In this thesis, we present a framework to address this problem of intermittent demand-supply mismatch using a 3-stage stochastic optimization model. We decide on the sourcing targets, the production plans based on supply realized, and finally, the dispatch plan based on orders received. As a case study, we analyze the operations and data from a private dairy company in eastern India, to understand the research problem and the applicability of the resulting model. We notice the impact of demand spikes and supply reduction in two areas: we increase supply targets in the periods preceding the demand spike; and we increase supply targets in periods when supply is expected to decrease, while demand is as usual. When there are multiple festival days within the time series, the compounding of impact depends on the sequencing of the events. / Finally, when we introduce the realistic constraint that the supply target needs to be constant throughout the time series, we see a degradation in the profitability, as we need to tradeoff between lost sales and wasted products. While the focus of this case study is the dairy industry, the conclusions from this research are broadly applicable to other industries dealing with perishables. / by Vishwanathan Parameshwaran lyer Nurani. / M. Eng. in Supply Chain Management / M.Eng.inSupplyChainManagement Massachusetts Institute of Technology, Supply Chain Management Program

Thesis: M. Eng. in Supply Chain Management, Massachusetts Institute of Technology, Supply Chain Management Program, 2019 / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 50-51). / The success of e-commerce continues to push the bounds of delivery services as customers expect near instant fulfillment at little additional cost. This demand for delivery performance and operational cost efficiency has led to the exploration of the last-mile delivery problem using creative multimodal delivery systems. One promising system consists of a truck that can carry and deploy multiple autonomous drones to assist in the fulfillment of customer demand. The contribution of this thesis is towards furthering the understanding of the application of autonomous flying drones in such a system and improve parcel delivery performance within the constraint of the current state of technology. This thesis explores the feasibility of deploying drones in last-mile delivery by modeling and then optimizing the cost of serving customers with a system consisting of one truck and multiple drones under multiple customer demand scenarios. While this optimization problem can be solved with mixed integer linear programming (MILP), the computation requirement is such that MILP is inefficient for real world scenarios with 100 or more customers. This research applies metaheuristic methodology to solve the truck-and-drone problem for scenarios with up to 158 customers in approximately 30 minutes of computation time. The test results confirm an average of 7% to 9% in savings opportunity for a 2-drone baseline over traditional single truck delivery tours. This savings opportunity is shown to vary with customer density, number of drones carried, range of drone flight, and speed of drone relative to speed of truck. / by Yue Kuang. / M. Eng. in Supply Chain Management / M.Eng.inSupplyChainManagement Massachusetts Institute of Technology, Supply Chain Management Program

Zugl.: Osnabrück, Universiẗat, Diss., 2007.