Despite recent advances in computer power and the development of better algorithms, theoretical scheduling methodologies developed for batch-chemical production are seldom applied in industry (Musier & Evans 1989 and Grossmann et al. 1992). Scheduling decisions may have significant impact on overall company profitability by defining how capital is utilized, the operating costs required, and the ability to meet due dates. The purpose of this research is to compare different production scheduling methods by applying them to a real-world multi-stage, multi-product, batch-chemical production line. This research addresses the problem that the theoretical algorithms are seldom applied in industry and allows for performance analysis of several theoretical algorithms. The research presented in this thesis focuses on the development and comparison of several scheduling algorithms. The two objectives of this research are to: 1. modify different heuristic production scheduling algorithms to minimize tardiness for a multi-product batch plant involving multiple processing stages with several out-of-phase parallel machines in each stage; and 2. compare the robustness and performance of these production schedules using a stochastic discrete event simulation of a real-world production line. The following three scheduling algorithms are compared: 1. a modified Musier and Evans scheduling algorithm (1989); 2. a modified Ku and Karimi Sequence Building Algorithm (1991); and 3. a greedy heuristic based on an earliest-due-date (EDD) policy. Musier and Evans' heuristic improvement method (1989) is applied to the three algorithms. The computation times to determine the total tardiness of each schedule are compared. Finally, all the schedules are tested for robustness and performance in a stochastic setting with the use of a discrete event simulation (DES) model. Mignon, Honkomp, and Reklaitis' evaluation techniques (1995) and Multiple Comparison of the Best are used to help determine the best algorithm. / Master of Science

This thesis consists of three self-contained essays in International Trade, Exchange Rates and Prices. Although independent, these essays share some common themes. The first two papers can be related to the vast literature on exchange rate pass-through to prices. While the first paper uses firm-product level data from Sweden to study firms’ export price response to movements in exchange rate, the second paper employs aggregate level data from Ethiopia and looks at the issue from the importers’ perspective. The third paper, like the first paper, uses Swedish firm-level data and investigates firms’ exporting behavior. The third paper, however, specifically focuses on export margins of multi-product firms and studies their response when exporting to destinations of different size and distance from the home country. / <p>At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 1: Manuscript. Paper 2: Manuscript. Paper 3: Manuscript.</p>

Doctor of Philosophy / Department of Agricultural Economics / Vincent Amanor-Boadu / Allen M. Featherstone / Estimation of cost functions can provide useful economic information to producers, economists, and policy makers. From the estimation of a cost function, it is possible to calculate cost efficiency, economies of scope, and economies of scale. Economic theory specifies the cost function as a frontier since firms cannot operate at lower cost than the cost minimizing input/output bundle. However, traditional parametric estimation techniques often violate economic theory using two sided-error systems. The stochastic frontier method has allowed the estimation of a frontier but continues to restrict the technology through functional assumption. Nonparametric frontier estimation is an alternative approach to estimate a cost frontier by enveloping the data which by its construct, conforms to economic theory. This research expands the economic information available by deriving multi-product scale economies and product-specific scale economies from the nonparametric approach. It also tests its ability to accurately recover these important economic measures under different assumptions of the cost function, and cost inefficiency distributions. Next, this new method is compared to other methods used to estimate cost functions and associated economic measures including a two-sided error system, stochastic frontier method, and an OLS model restricting the errors to take on only positive values. Finally, the nonparametric approach with the new measures is applied to a sample of Kansas farms. The nonparametric approach is able to closely estimate economies of scale and scope from estimation of a cost frontier. Comparison reveals that the nonparametric approach is closer to the “true” economic measures than some parametric methods and that it is better able to extrapolate out of sample when there are no zero output firms. Finally, the nonparametric approach shows that potential cost savings from economies of scale and economies of scope exist for small Kansas farms. However, cost savings from economies of scale become exhausted when farms exceed gross annual revenues of $500k, while economies of scope also diminish as farms grow larger. Results also show from annual frontier estimations that estimates of economies of scale, scope, and cost efficiency have remained relatively stable from 2002 to 2011.

Revenue Management (RM) has become one of the most successful application areas of Operation Research. What started off as an obscure practice among few airlines in U.S in early seventies, has attained the status of mainstream business practice, thanks to the major success enjoyed by companies applying RM. Over the same period, academic and industrial research on the methodology of RM has also grown rapidly. Despite the vast technical literature on the subject of revenue management, relatively few papers explicitly model the customer’s choice behavior. Such a behavior of customers could have major impact on revenue realized by an organization. Motivated by this, we focus on addressing the problem faced by a seller who serves customers exhibiting buy-down behavior. We address two important problems faced by a seller with few perishable goods. His objective is to obtain maximum revenue possible by sales of his perishable goods. The seller now potentially faces the problem of fixing the price of the products and then control the availability of products so as to maximize his revenue by minimizing the number of customers who buy-down. The first problem is the multi-product pricing problem where we consider a monop- olistic market situation in which a seller has some quantities of perishable goods under his disposal. The seller has the option of adding few additional features to the base product(perishable good) and thereby differentiating the products to cater to different market segments. Adding each additional feature involves certain cost and there are no restrictions on the availability of the features except that a feature can be added to the base product atmost once . The customers are price-sensitive and the seller is aware of the price-demand relationship of the various customer segments. A customer looking for a product buys the product if and only if the price is less than his reservation price. The sellers’ problem is to identify the price and bundling of features for the various customer segments so as to generate maximum possible revenue. We develop a Mixed integer non-linear mathematical programming model for the problem. We then split the problem into pricing problem and bundling problem and solve them sequentially. We finally provide a numeric example to illustrate the solution procedure. Once the prices are fixed, the next problem is to control the availability of products so as to prevent the buy-down behavior of the customers. We deal with the situation of a seller with two substitutable products. The price of both products are fixed over entire selling period. In a traditional control mechanism structure if the sequence of arrival of customers are known, then it becomes trivial to solve the problem of setting control limits which would prevent buy-down behavior. But in reality it never happens that the seller knows the arrival sequence. Hence in this study to isolate the effect of arrival sequence from other complexities like demand variability, we assume a deterministic demand for both the products but the arrival sequence is randomized. We initially analyze the above described problem and develop a static control mech- anism. We show that the static control mechanism is asymptotically equivalent to the traditional selling mechanism. Then we move on to make modification in the static con- trol mechanism and make it a dynamic control mechanism such that it will respond to the buy-down customers. In order to analyze the performance of dynamic control mechanism, we build a simulation model that would compare traditional selling mechanism and dynamic control mechanism. Statistical analysis is then done on the simulation results. It is shown that for all values of buy-down proportion, on an average the dynamic control mechanism outperforms the traditional control mechanism. Further there is a trend in revenues generated depending upon the buy-down proportion which is also explained. The chapter concludes with operating guidelines for better revenue realization. The organization of the thesis is as follows. In chapter 2, we present the literature survey. We start off with the history of RM and proceed to discuss the inventory control problems in RM in detail. Then we discuss literatures dealing with customer choice behavior. In chapter 3, we define and model the multi - product pricing problem. We present a mixed integer non-linear mathematical program to model the pricing problem. The solution to this problem is divided into two sub problems - the pricing problem and the bundling problem. Solution methodologies for both sub - problem are given and the chapter concludes with a numerical illustration for a 3 - product pricing problem. In chapter 4, we define and address the inventory control problem for a two product case when customers exhibit buy-down nature. We develop a static control mechanism and study its properties. Then we move on to the dynamic control mechanism which would suit real - world conditions. Finally we study the quality of developed methodology using statistical testing methods.

第一章緒論，介紹俱樂部財理論發展背景，並且定義俱樂部的正確範疇。第二章基于 個人效用函數相同之假定，以個體的觀點，用數學及幾何模型來探討說明俱樂部財的 最適提供條件及會員條件。第三章放寬個人效用函數相同之假定，而以整體經濟的觀 點，來探討分析比較與前章各項條件之異同。第四章則探討現存有關文獻的一些具爭 論性的觀點；並且評介歧視性俱樂部（discriminatary club ）與多財貨俱樂部（m- lti-product club）之模型。第五章則利用遊戲理論的觀點，來檢討俱樂部內及俱樂 部之間的穩定性問題。第六章結論，總結本文的觀點，並且提示未來可能研究之方向 。 本文研究的動機乃在于，俱樂部理論已蔚為經濟、財政理論之重要一環。其研究方法 結合福利經濟學、公共財政、遊戲理論。其本身可提供地方公共財、政治軍事聯盟、 公共事業定價．．．等之研究基礎，因此乃撰此文，期有助學術界瞭解俱樂部理論之 內涵。