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Cumnt research studies in cellular manufacturing have considered environments constrained only by the machine resource, when in fact the flexibility of manufacturing cells is derived mainly from its allocation of the labor resource. This research specifically examines the labor resource in cellular manufacturing, also known as p u p technology (GT), through a wries of simulation experiments on a hypothetical GT shop and recommends conditions under which different labor allocation strategies may be appropnate. The effects of various product routings and scheduling policies on labor allocation are also examined.

The Japanese "just-in-time with kanban" technique reduces in-process inventory to absolute minimal levels, in concert with the Japamse belief that inventory is an unnecessary evil. Due to the succas of Japanese firms that employ this type of system. American firms would like to import this technique and emulate Japanese successes. But this Japanese succus may be attributable not only to the just-in-time with kanban technique but also to the production environment in which the technique is employed. This paper simulates the just-in-time with kanban technique for a multiline, multistage production system in order to determine its adaptability to an American production environment that might include such characteristics as variable procasing tima, variable master production scheduling, and imbalances between production stages. The results have practical implications for those firms considering adoption of the Japanese technique. Stb1-t A m * lk&i!tbn/@mtionr Marmgment, ShuMon, Inventory Management, and Netwarb.

In order to compete favorably in the world markets, it is essential for a company to have an efficient and flexible manufacturing system, capable of producing quality products with low costs and reacting quickly to the changes in consumer demand. Factory automation (FA) (a very popular term in Japan and virtually synonymous with computer integrated manufacturing (CIM)) has been recognized as a promising approach for companies to become more competitive. Currently, the United States may still lead the world in developing automation technologies; however, Japan has been more successful in implementing them. If factory automation holds the key to the revival of American industrial competitiveness, why has there been a lack of actual implementation? To answer this question, it is beneficial to explore the approaches that Japanese companies have employed to implement factory automation. The main objective of this paper is to report the findings of a research study that investigates the practical experience that Japanese industries have accumulated concerning the implementation of factory automation.

This document is dedicated to my entire family, but especially to Amanda, Conner, mom and pawpaw. Amanda and Conner provided me with the necessary strength, determination and never ending support and were my inspiration in pursuing and finishing my PhD. Mom and pawpaw are, without a doubt, the two most influential people in my life. For good and for bad, everything that I am is as a result of my never ending effort to model myself after these two amazing people. Pawpaw was the kindest and most sincere person that I have ever met and although he's in a better place now, I still think of him every day. My mother is the strongest and hardest working person that I know and without her many sacrifices, my life could have been completely different and I would never have had the opportunity to achieve this goal. Thank you! iv ACKNOWLEDGMENTS I would like to especially thank my wife Amanda for supporting and putting up with me throughout this process. I know that it was not easy. I would also like to thank our families for their never ending support throughout this very challenging endeavor. In addition, I would like to thank my dissertation committee and the DIS department staff for their support and guidance. In particular I would like to thank and acknowledge my advisor, Anurag Agarwal, and my co-chair, Praveen Pathak, for their countless hours of training and support. I couldn't have done it without you!! v

Given the NP-Hard nature of many optimization problems, it is often impractical to obtain optimal solutions to large-scale problems in reasonable computing time. For this reason, heuristic and metaheuristic search approaches are used to obtain good solutions fast. However, these techniques often struggle to develop a good balance between local and global search. In this paper we propose a hybrid metaheuristic approach which we call the NeuroGenetic approach to search for good solutions for these large scale optimization problems by at least partially overcoming this challenge. The proposed NeuroGenetic approach combines the Augmented Neural Network (AugNN) and the Genetic Algorithm (GA) search approaches by interleaving the two. We chose these two approaches to hybridize, as they offer complementary advantages and disadvantages; GAs are very good at searching globally, while AugNNs are more proficient at searching locally. The proposed hybrid strategy capitalizes on the strong points of each approach while avoiding their shortcomings. In the paper we discuss the issues associated with the feasibility of hybridizing these two approaches and propose an interleaving algorithm. We also provide empirical evidence demonstrating the effectiveness of the proposed approach.

Worldwide growth of the online community continues to push the popularity of internet marketing. Fueled by this trend, the online advertising industry is experiencing unprecedented revenue growth. One of the most important drivers of this revenue is banner advertising, which has long been a staple of the online advertising industry. Previous research has introduced quantitative models and solution approaches for the challenging basic scheduling optimization problem. We extend this work by incorporating the most common and popular trend in the in the industry, online advertisement targeting. In addition, motivated by the NP-hard nature of the resulting problem, we propose and test several heuristic and metaheuristic based solution techniques for the proposed problem.

Over the last decade, telecommunications companies have invested nearly 100 billion dollars in the development of an impressive fiber optic backbone which is capable of transmitting data at incredible speeds. However, much of this backbone remains unused because of the data capacity bottleneck which exists at the user level. While various technologies have emerged to provide greater end-point capacity, many of these are of limited availability due to cost or technical considerations. One promising technology has been high-speed wireless service. Wireless service has the potential to provide widespread coverage, but the cost of developing the infrastructure such as antenna towers can be formidable. While models have been developed to assist in the planning for minimum cost tower placement, these models can be quite large and complex to solve. This paper explores alternate solution methods based on heuristic approaches which may allow for the solution of much larger tower placement problems.

One strategy for alleviating excess latency (delay) in the Internet is the caching of web content at multiple locations. This reduces the number of hops necessary to reach the desired content. This strategy is used for web content such as html pages, images, streaming video, and Internet radio. The network of servers which store this content, and the collections of objects stored on each server, is called a content distribution network (CDN). In order to optimally design a CDN, given a network topology with available server storage capacity at various points in the network, one must decide which object collections to place on each server in order to achieve performance or cost objectives. The placements must be within the storage limits of the servers and must reflect the request patterns for each collection of objects to be cached. Researchers have suggested formulations for the CDN problem which address performance by minimizing latency (the average number of hops is a commonly accepted measure of latency) from client to content, or formulations that focus on minimizing cost of storage and/or bandwidth. In this research, we develop a model which allows for the simultaneous treatment of performance and cost, present examples to illustrate the application of the model and perform a detailed designed experiment to gain insights into cost/hops tradeoff for a variety of network parameters.

Many medical organisations around the world have connected themselves in supply chains, and are exploring the strategic utilisation of information technology (IT) throughout their chains to improve their overall efficiency and effectiveness. Although these efforts may reduce health costs, both the current status of IT security risk and the potential consequences of interconnectedness are largely unknown. This research examines medical supply chain risk exposure. In particular, data from six pharmaceutical companies and eight healthcare organisations is combined with input from security experts to determine the current degree of IT security risk. In addition, we examine an optimal strategy to reduce overall risk and the amount of supply chain risk due to partnering. We find, for the surveyed organisations, a dramatic under-deployment of controls, resulting in huge risk exposure.

In this paper, we analyze the prevalence and frequency of email marketing among 200 of the largest franchise corporations in the United States, and compare the deliverability of emails in various industries-that is, how often legitimate, solicited emails were regarded by major hosted email providers as spam. We found that approximately half (45 per cent) of large franchise corporations provide opt-in email marketing newsletters, with email marketing being most popular in the hotel and health care industries and least popular in the pet and maintenance industries. Most corporations sent an average of one email every 10 weeks, predominantly on weekdays. Companies in the hotel and food industries were the most prolifi c email marketers, and hotels showed an unusual proclivity for emailing on Sundays. Surprisingly, an astonishing one-third of legitimate emails, on average, were fl agged as spam by major email hosting providers. Food and automotive companies were most susceptible to deliverability issues, and hotel and personal care companies were relatively immune to deliverability problems. Our results provide an interesting comparison of the email marketing habits of large US franchise companies in a variety of industries, and suggest a variety of questions and action items for digital marketing professionals.

The Northridge earthquake of 1994 displaced almost 10,000 families and destroyed major transportation infrastructure within Southern California, and Hurricane Katrina created the largest national housing crisis since the Dust Bowl of 1930, destroying over 300,000 homes and leaving over one million people seeking shelter. Numerous smaller disasters each year such as tornados, costal or inland flooding, and less severe earthquakes also destroy homes and displace families, although on a much smaller scale. Arranging housing for disaster victims ranks as a top priority after the immediate needs for food and medical care are met. This task becomes more challenging as families are displaced for a longer period of time due to increases in costs, government involvement, and expectations of the victims. In early 2009, FEMA released the first-ever National Disaster Housing Strategy which calls for improved planning and outlines the key principles and policies guiding disaster sheltering, interim housing, and restoration of permanent housing. While all three housing problems are very difficult, the provision of adequate temporary or interim housing is perhaps the most challenging. A few researchers have addressed the issue of optimal allocation of temporary housing, but have focused primarily on the first part of the problem which focuses on the selection of adequate capacity from among available interim housing alternatives. The second part of the problem, which consists of recommending housing alternatives to individual families from the pool of temporary housing units selected in phase one such that educational, healthcare, and socioeconomic needs are met, has not yet been addressed to the best of our knowledge. We propose a decision support system for assigning families to housing units which addresses these needs. We develop a benchmark integer programming model for developing a balanced housing plan, and then use the model to evaluate three heuristics which could be practically applied with our system. We use a prototypical example to illustrate the model and evaluate the heuristics, and to demonstrate their appropriateness for the development of realistic real-time housing recommendations.

The online advertisement publishing industry is a rapidly growing multi-billion dollar industry. Organisations in this industry generate revenue by creating and/or acquiring online advertising space that they can sell at a profit. Their success is directly dependent on the effectiveness of their publishing strategy in terms of its ability to create traffic and interest for their clients by delivering advertisements which are closely in line with the recipient's interests. We propose a supervised learning based ad targeting technique which will help online advertisement publishers achieve this goal. Empirical tests of the new technique are very promising.

Baseball, like most other sports, has a set of tenets that began early and have survived virtually unquestioned. Modern analytics gives us an opportunity to examine some of these long-held tenets to see if they were founded on solid evidence. This research examines some common baseball wisdom through an initial study utilizing simulation. In particular, the profiles of several baseball teams are constructed and various factors are examined by simulating ten baseball seasons under various configurations with the different teams. Contrary to conventional wisdom, a batting order where high-average hitters bat third in a lineup and the team's best power hitter bats cleanup (fourth), for example, does not necessarily generate the most runs per game over the long run. Moreover, high-average hitters with less power can generate more runs per game than power hitters with lesser averages. Finally, it appears that hitters who perform well with runners in scoring position are more influential in helping their team score more runs than even more powerful or higher average hitters who do not produce as frequently in such cases. Players with lower star profiles, but who rise to the occasion with runners in scoring position, can often be purchased by baseball clubs that have a more constrained payroll; teams that are less well-off financially may thus purchase or trade for these hitters and still field a team with a competitive level of high run production.

This paper addresses the task scheduling problem which involves minimizing the makespan in scheduling n tasks on m machines (resources) where the tasks follow a precedence relation and preemption is not allowed. The machines (resources) are all identical and a task needs only one machine for processing. Like most scheduling problems, this one is NP-hard in nature, making it difficult to find exact solutions for larger problems in reasonable computational time. Heuristic and metaheuristic approaches are therefore needed to solve this type of problem. This paper proposes a metaheuristic approach - called NeuroGenetic - which is a combination of an augmented neural network and a genetic algorithm. The augmented neural network approach is itself a hybrid of a heuristic approach and a neural network approach. The NeuroGenetic approach is tested against some popular test problems from the literature, and the results indicate that the NeuroGenetic approach performs significantly better tha...

The multi-dimensional knapsack problem (MDKP) is a well-studied problem in Decision Sciences. The problems NP-Hard nature prevents the successful application of exact procedures such as branch and bound, implicit enumeration and dynamic programming for larger problems. As a result, various approximate solution approaches, such as the relaxation approaches, heuristic and metaheuristic approaches have been developed and applied effectively to this problem. In this study, we propose a Neural approach, a Genetic Algorithms approach and a Neurogenetic approach, which is a hybrid of the Neural and the Genetic Algorithms approach. The Neural approach is essentially a problem-space based non-deterministic local-search algorithm. In the Genetic Algorithms approach we propose a new way of generating initial population. In the Neurogenetic approach, we show that the Neural and Genetic iterations, when interleaved appropriately, can complement each other and provide better solutions than either...

Fitness technologies are a prominent example of the societal trend towards personal informatics. These technologies pair devices that have various embedded sensors with one or more apps to allow for the collection, analysis, socialization, and management of individuals' health and wellness data. We have limited insight into what drives the use of fitness technologies or how they may contribute to wellness outcomes. To address this gap, our study examines how

Fitness technology feature use items were not available in the literature, and thus, were developed for the current study. Items were developed for each feature set following the procedure described next. We used a four-step process to determine the fitness technology features that make up our first-order subconstructs. First, we compiled a list of currently available fitness devices and their associated apps using lists of wearables published in popular media outlets. The original list contained 72 devices and was compiled using lists of wearables from CNET, PC Magazine, The Wall Street Journal, Engadget, Gizmodo, and others. While not comprehensive, the redundancy across multiple lists suggests that our list, at the very least, contains the most popular devices in the wearables category at the time the data was collected. Second, the three researchers independently visited every website of each device/app on the list and collected the features the company advertised for the fitness technology. Third, all three of the researchers' feature lists were compared, discussed, and used to create an integrated list. Fourth, once survey items were created, an expert panel was convened to examine the feature list and scales as described below. Accepted procedural methods (Churchill 1979; MacKenzie et al. 2011) were followed in developing the fitness technology use items. Once the items were developed, an expert panel was convened. The expert panel consisted of two faculty members who are well versed in surveybased methodologies, two faculty members who were active users of fitness technologies, and two employees of a fitness technology company. The expert panel was instructed to examine the entire survey instrument for clarity and to provide feedback on wording and note if any fitness technology features were missing. The expert panel did not provide any new fitness technology features, which indicated our list was reasonably comprehensive. The expert panel did suggest wording changes to the fitness technology features set use items and the addition of a few more fitness device and apps to our list (primarily new versions of devices already present in our list). We compiled the expert panel wording suggestions and considered each suggestion. Most wording suggestions from the expert panel were implemented, improving the clarity of the survey items.

Sport venue naming rights agreements represent monumental longterm marketing investments to increase brand awareness and improve a firm's image. These agreements require enormous expenditures, highlighting the importance of understanding their impact on the firm's market value. Questions of the wisdom of such investments today, which types of sport venues are most appropriate, and whether full corporate names or truncated ones are equally successful are of more than academic interest. Prior research has presented only a limited window into the efficacy of these deals. Results from the well-known event study methodology show improved stock market returns based on 122 announcements of naming rights deals, although it is found that market reactions have soured since 2001, when several firms investing in naming rights experienced insolvency. Investments in naming major league baseball or multi-sport venues have been particularly wise. Somewhat surprisingly, we observe that longer sport venue names are preferred to other name lengths.

Estimating the potential loss from a disaster can be a difficult task due to the great uncertainty plus a lack of historical data. An integer programming budgeting system is developed for pre-disaster planning and mitigation funding where the loss parameters of the decision model are fuzzy numbers based on expert opinion. It allows for two options for representing the fuzzy numbers: the element with the highest grade of membership (the loss level that the expert feels about most strongly) and the element corresponding to the fuzzy average value at risk (AVaR) (a loss level with minimal support, but devastating consequences). A plan based on weighted preferences provides a compromise, using mitigation strategies based on maximum membership and strategies based on AVaR. Comparisons are made to illustrate how the budgeting model could be used to determine the best combination of strategies and weights for allocating mitigation dollars to balance overall risk.

Internet popularity is at an all time high. This phenomenon continues to drive enormous revenue growth for the online advertising industry. One of the difficult challenges facing this industry is determining how to schedule online advertisements. We extend prior research in this area by developing a quantitative model which incorporates a very important economic strategy, volume pricing discounts. In addition, motivated by the NP-Hard nature of the problem, we propose and test a several heuristic and metaheuristic solution approaches. We show that explicit consideration of this economic pricing strategy in the scheduling process can, under certain elasticity of demand assumptions, significantly improve the revenue generation ability of online ad publishers. This provides significant support for the proposed model.