Thesis (Ph. D.)--Technische Universitat, Berlin. / Title from e-book title screen (viewed January 2, 2008). Includes bibliographical references (p. [217]-240).

Thesis (M.S.)--Ohio University, November, 2004. / Title from PDF t.p. Includes bibliographical references (p. 93-108)

No description available.

by Arnoldo C. Hax and Harlan C. Meal. / Bibliography: leaves 20-21.

The Master’s thesis analyses the production planning in chosen company. Theoretical part focuses on terms, which are necessary to understand to deal with the issue of production planning. The practical part contains an analysis of the current state of production planning in the company, designs and their benefits to improve in this area.

This thesis deals with adding planning to the current information system as requirement by the company. The theoretical part describes the methodes of information systems for the production plan. These tools are mostly general and trying to cover the entire spectrum of manufacturing processes. The practical part is devoted to implementing of the produciton planning. The modul planning is incorporated into the current information system.The modul planning has been implementing for efficiency of the systemand faster throughput of the orders the company.

No description available.

No description available.

The job shop scheduling problem, in which we must determine the order or sequence for processing a set of jobs through several machines in an optimum manner, has received considerable attention. In this paper a number of the methods and techniques are reviewed and an attempt to categorize them according to their appropriateness for effective use in job shop scheduling has been made. Approaches are classified in two categories: a) analytical techniques and b) graphical methods. Also, it should be noticed that this report does not include all the attempts and trials, especially the heuristic approaches.

JS McMillan Fisheries Ltd. (JSM) is a Vancouver-based company with operations in nearly all levels of the commercial fishing industry, from supply through distribution. The heart of the operation is the processing facilities where freshly caught Pacific salmon are prepared for sale to end consumers and institutional buyers. As the operations of JSM evolved, the decision making for allocating a catch of salmon with varying characteristics amongst a set of final products has become too complex and time consuming. The focus of this study is to determine an effective and efficient method for JSM to allocate daily a fresh salmon harvest between the various products they produce on a daily basis. The goal is short-term production planning, to allocate the catch among the products in such a manner that the profit potential of the catch is maximized, i.e. prepare a production schedule that maximizes the total profit over the planning horizon. Additional goals of this project include: automation of the decision making process for the catch allocation, "what if" planning, decreasing expert dependency, reducing decision making time, and building a practical and innovative decision support tool. In order to solve this problem efficiently and effectively, optimization models were developed for allocating the catch to the end products. A corresponding decision support tool was built for the end-users at JSM.