Theses and Dissertations - Department of Information Systems, Statistics & Management Science
http://ir.ua.edu/handle/123456789/114
2020-11-26T15:50:14ZDistribution system design for omnichannel retailing
http://ir.ua.edu/handle/123456789/6463
Distribution system design for omnichannel retailing
Guo, Jia
Omnichannel retailing - serving customers via a combination of physical stores and web-based stores- offers new opportunities and forces traditional retailers to rethink their supply chain design, operational efficiency, revenue/cost streams, and operations/marketing interface. While omnichannel supply chain management has received some attention recently, the role of cross-channel fulfillment, the layout of the omnichannel retail supply chain, and revenue management considering customer channel choice behavior have not been widely studied. This dissertation investigates these three streams in omnichannel supply chain design. In the cross-channel fulfillment stream, we study the optimal supply chain design for a dual-channel retailer that combines the operations of both channels in an omnichannel environment considering demand segmentation, cost structure, and more importantly, the execution ability of the firm. We formulate this problem as a two-stage stochastic programming model and use first-order optimality conditions to study the optimal inventory replenishment decisions and omnichannel strategy decisions under perfect and imperfect demand information. For the second chapter, we extend the dual-channel setting from a single store to N retail stores. We study the transshipment problem based on a two-store case by reformulating the problem into a large scale mixed-integer linear programming model. The third chapter addresses the revenue management stream by focuses on the interface between the retailer's operations and customer's demand. Specifically, this chapter explores the right role for a physical store in an omnichannel environment for an online-first retailer. The main result relates to the trade-off between the increased profits from the newly acquired demand (from the new channel) and the increased fulfillment and operations costs from cannibalized demand.
Electronic Thesis or Dissertation
2019-01-01T00:00:00ZOn the use of transformations for modeling multidimensional heterogeneous data
http://ir.ua.edu/handle/123456789/6464
On the use of transformations for modeling multidimensional heterogeneous data
Sarkar, Shuchismita
The objective of cluster analysis is to find distinct groups of similar observations. There are many algorithms in literature that can perform this task and among them model based clustering is one of the most flexible tools. Assumption of Gaussian density for mixture components is quite popular in this field of study due to it’s convenient form. However, this assumption is not always valid. This thesis explores the use of various transformations for finding clusters in heterogeneous data. In this process, the thesis also attends to several data structures such as vector-, matrix-, tensor-, and network-valued data. In the first chapter, linear and non-linear transformations are used to model heterogeneous vector-valued observations when the data suffer from measurement inconsistency. The second chapter discusses an extensive set of parsimonious models for matrix-valued data. In the third chapter a methodology for clustering skewed tensor-valued data is developed and it is applied for analyzing remuneration of professors in American universities. The fourth chapter focuses on network-valued data and a novel finite mixture model addressing the dependent structure of network data is proposed. Finally, the fifth chapter describes the functionality of a R package “netClust” developed by the author for clustering unilayer and multilayer networks following the methodology proposed in Chapter four.
Electronic Thesis or Dissertation
2019-01-01T00:00:00ZDiscernable Periods in the Historical Development of Statistical Inference
http://ir.ua.edu/handle/123456789/6234
Discernable Periods in the Historical Development of Statistical Inference
Gober, Richard Wayne
The purpose of this study is to trace the historical development of that part of modern statistical procedures known as statistical inference. Although the application of statistical methods is concerned more than ever with the study of great masses of data, percentages, and columns of figures, statistics has moved far beyond the descriptive stage. Using concepts from mathematics, logic, economics, and psychology, modern statistics has developed into a designed "way of thinking" about conclusions or decisions to help a person choose a reasonable course of action under uncertainty. The general theory and methodology is called statistical inference.
1967-01-01T00:00:00ZStochastic decision models for last mile distribution using approximate dynamic programming
http://ir.ua.edu/handle/123456789/5337
Stochastic decision models for last mile distribution using approximate dynamic programming
Cook, Robert A.
After localized disasters, donations are sometimes collected at the same facility as they are distributed, and the damaged infrastructure is overwhelmed by the congestion. However, separating the donation facilities from the points of distribution requires a vehicle to bring items between locations. We investigate dispatching policies for vehicles in such a scenario. We initially consider the case with one collection facility called a Staging Area (SA) and one Point of Distribution (POD). Among other things, we prove that if we have two or more vehicles, it is optimal to continuously dispatch the vehicles under most circumstances. Furthermore, we define two common-sense practical decision policies - Continuous Dispatching (CD) and Full Truckload Dispatching (FTD) - and demonstrate that CD performs well for one vehicle, at least as well as FTD across the board. This begs the question, can CD work on larger, more realistic networks? To answer this, we expand our network to two SAs and two vehicles to best compare to our prior work. First, we evaluate two Value Function Approximation methods and find that Rollout Algorithms can serve as a proxy for the optimal solution. Against this as a benchmark, CD performs well when the amount of items donated greatly exceeds the demand, and also when demand exceeds supply, but struggles when the two are equivalent. Next, we expand our network and consider general numbers of SAs and vehicles. Before we can begin, we must redefine CD for the expanded network. We describe several variations of CD for general networks, requiring different information to implement. So, by comparing them, we evaluate the value of the different pieces of information that a practitioner may have in the field. We find that visiting each SA equally on a rotating basis is a powerful strategy, although a better approach can be found by combining information about inventory levels, the locations of the vehicles, and the expected accumulation at each SA. Given the chaotic nature of humanitarian logistics, it is unlikely that this information may be obtained accurately, and so we recommend the rotating strategy.
Electronic Thesis or Dissertation
2018-01-01T00:00:00Z