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Supply chain scheduling (SCS) emerged as a result of the integrated Supply Chain Management concept and should be incorporated in planning and operating Supply Chain (SC). The review of literature indicated integration of SCS in the SC is still far from being achieved. Recognising that optimisation of scheduling activities separately will only lead to local optima, this research proposes a SCS global optimisation through the integration of scheduling within manufacturing and distribution networks. / Thesis (PhD)--University of South Australia, 2008.

This thesis discusses the use of inventory pooling methods in inventory management for the so-called multi-location systems whereby the stocking locations share their inventories, typically by using lateral transhipments, in order to fill demand at a stock-out retailer with supplies from another having surplus items. The capability of conventional pooled-inventory systems are upgraded with the proposal herin of a novel approach that employs emergency orders along with lateral transshipments to improve network performamce under a high shortage-penalty environment. / Thesis (PhD)--University of South Australia, 2008.

Thesis (M.S.)--School of Economics, Georgia Institute of Technology, 2005. Directed by Patrick McCarthy. / Patrick McCarthy, Committee Chair ; Dr. Haizheng Li, Committee Member. Includes bibliographical references.

Thesis (Ph.D)--Industrial and Systems Engineering, Georgia Institute of Technology, 2009. / Committee Co-Chair: Ergun, Ozlem; Committee Co-Chair: Savelsbergh, Martin; Committee Member: Erera, Alan; Committee Member: Ferguson, Mark; Committee Member: Keskinocak, Pinar. Part of the SMARTech Electronic Thesis and Dissertation Collection.

Thesis (Ph. D.)--University of Oregon, 1999. / Typescript. Includes vita and abstract. Includes bibliographical references (leaves 168-173). Also available for download via the World Wide Web; free to University of Oregon users. Address: http://wwwlib.umi.com/cr/uoregon/fullcit?p9948030.

Thesis (Ph. D.)--Columbia University, 1993. / Includes bibliographical references (leaves 174-183).

Thesis (Ph. D.)--University of Wisconsin--Madison, 1983. / Typescript. Vita. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 74-76).

Thesis (MScEng (Industrial Engineering))--University of Stellenbosch, 2005. / This thesis introduces an adaptation of the Population-Based Incremental Learning (PBIL) meta-heuristic implemented on a variant of the General Pickup and Delivery Problem. The mapping of the customers in the problem and the vehicle routes on a time grid enables the utilization of the powerful genetic search that the PBIL algorithm provides in liaison with competitive learning. The problem consists of a number of customers who may at any time of the day place an order on another customer for some package. The fleet of vehicles travelling between the customers must then combine powers to pickup and deliver the package as fast as possible without ever leaving their assigned routes. The solution to this problem then, is a set of routes for the fleet that will minimize some percentile of the delivery times between customers. The PBIL meta-heuristic provides the blueprint of the final algorithm, where the final algorithm is actually just a normal PBIL algorithm with some external solution generation and evaluation techniques employed. The final algorithm can easily solve an instance of the problem in polynomial time, given that the resolution of the time grid used is not too small.

There is a great need for a pharmaceutical manufacturer to provide its customers with the right product at the right time, place and price and also to deliver the product in the right quantity and quality. Should pharmaceutical customers not receive their orders on time from the pharmaceutical manufacturer, the customers might face out-of-stock situations. As a result, the patients or customers might turn to an alternative product from a different pharmaceutical manufacturer, which has the required stock readily available. This could lead to loss in sales and even death amongst its customers. The main objective of this study was to determine the key factors that form part of the demand and operations planning strategies to ensure that these factors are in place to effectively manage and execute the supply chain and logistics processes to reduce possible out-of-stock situations amongst its customers. As a starting point to the study, an analysis was performed based on the review of relevant research and literature from various text books, journals, publications, as well as internet sources. The literature study covered various aspects such as demand planning, production planning, the use of different demand and operations planning strategies, as well as the importance of continuous internal and external customer service levels to ensure that customer orders are delivered on time. The analysis of the literature review was used to establish a theoretical basis for the design and structure of the questionnaire that was used as a research instrument in this study. A survey was conducted amongst the employees that are responsible for executing the supply chain and logistics processes within Aspen Pharmacare. These employees resided within the three main departments of the pharmaceutical manufacturer, namely, the Demand and Operations Planning, Production and Packing, as well as the Warehouse and Distribution departments. Each question posed in the questionnaire related to the role of each employee within these departments that are responsible for the logistics processes within Aspen Pharmacare. The empirical results from the study indicated that the respondents were in support that specific key factors are important for a pharmaceutical manufacturer to manage incoming customer orders efficiently and effectively to reduce possible out-of-stock situations amongst its end customers. However, the respondents also highlighted that there were a number of obstacles preventing them from implementing the key factors that are required to manage incoming customer orders more efficiently within the pharmaceutical manufacturer. Some of these obstacles include: the lack of pro- activeness; lack of accountability; and the lack of constant communication between the employees from the three main departments. Furthermore, incomplete hand-over information during shift changes amongst the employees of the Production and Packing department created unnecessary down-time. Also, the employees from the Warehouse and Distribution department were not informed timeously when changes to the production schedule were made. These obstacles will have a negative impact on the ultimate customer delivery dates and need to be addressed. The empirical results highlighted some recommendations to assist pharmaceutical manufacturing companies to more effectively and efficiently manage their incoming customer orders to reduce or eliminate any possible out-of-stock situations amongst its end customers. Some recommendations include: improved communication between the three main departments; to react immediately to out-of-stock products; and to ensure that internal and external customer service levels are adhered to at all times. The implementation of the recommendations based on the empirical findings of the study will assist the pharmaceutical manufacturing company to achieve excellence and to become a world-class supplier of generic pharmaceutical products. In this way, all incoming customer orders can be fulfilled on time.