Recent advances in the theory and practice of logical analysis of data

Logical Analysis of Data (LAD) is a data analysis methodology introduced by Peter L. Hammer in 1986. LAD distinguishes itself from other classification and machine learning methods by the fact that it analyzes a significant subset of combinations of variables to describe the positive or negative nature of an observation and uses combinatorial techniques to extract models defined in terms of patterns. In recent years, the methodology has tremendously advanced through numerous theoretical developments and practical applications. In the present paper, we review the methodology and its recent advances, describe novel applications in engineering, finance, health care, and algorithmic techniques for some stochastic optimization problems, and provide a comparative description of LAD with well-known classification methods

Managing Emerging Market Operations

Emerging markets have been a critical part of global business, with high share of global GDP and rapid economy growth. My dissertation research focuses on studying risks and opportunities in emerging market operations. One critical characteristic of emerging markets is that agriculture remains an essential sector. The world looks to emerging countries to meet the increasing food demand. However, the output remains significantly below the potential due to limited financial, technology and policy support. Scientific agriculture such as effective planting and mechanization could potentially help farmers achieve higher yields. In the first chapter of my dissertation, we study the optimal seeding policy under rainfall uncertainty. Utilizing field weather data from Southern Africa, we investigate the advantage of the optimal planting schedule and the impact of climate conditions on this advantage in a real-size large-scale problem. Another critical characteristic of emerging markets is the low labor cost. This makes emerging markets attractive bases for global manufacturing and service operations. However, the globalization of supply chains complicates the logistics and procurement operations. In the second chapter, we focus on the warehouse outsourcing strategy in global supply chains. We establish the optimal warehousing strategy and demonstrate that excluding the logistics dynamics from contracting and making warehousing decisions unilaterally afterwards can lead to a suboptimal warehousing strategy for the retailer. Furthermore, a variety of threats such as supplier failure and transportation disruption could delay or even disrupt the operations, offsetting the low-cost benefit of emerging economies. In the third chapter, we study the optimal sourcing strategy under disruption in global supply chains. We establish the optimal sourcing strategy and provide insights on the roles of the nearshore supplier in response to supply chain disruption. Overall, my dissertation concentrates on the application of scientific methods to planting and farm machinery procurement to improve agricultural productivity in Africa and leveraging low-cost benefits in emerging markets.Doctor of Philosoph