Modeling and solving the single facility line restoration problem

"April 1998."Includes bibliographical references (p. 40-42).by A. Balakrishnan ... [et al.]

Polyhedral properties of the network restoration problem-with the convex hull of a special case

"November 1997."Includes bibliographical references (p. 27).by T.L. Magnanti and Y. Wang

Optimization in Telecommunication Networks

Network design and network synthesis have been the classical optimization problems intelecommunication for a long time. In the recent past, there have been many technologicaldevelopments such as digitization of information, optical networks, internet, and wirelessnetworks. These developments have led to a series of new optimization problems. Thismanuscript gives an overview of the developments in solving both classical and moderntelecom optimization problems.We start with a short historical overview of the technological developments. Then,the classical (still actual) network design and synthesis problems are described with anemphasis on the latest developments on modelling and solving them. Classical results suchas Menger’s disjoint paths theorem, and Ford-Fulkerson’s max-flow-min-cut theorem, butalso Gomory-Hu trees and the Okamura-Seymour cut-condition, will be related to themodels described. Finally, we describe recent optimization problems such as routing andwavelength assignment, and grooming in optical networks.operations research and management science;

Survivable network design with stepwise incremental cost function

Modern society has become more and more dependent on information services, transferred in both public and private network, than ever before. The use of integration of computers with telecommunications has created a so-called “Information Age”. The advent of high capacity digital telecommunication facilities has made it possible for the huge amount of traffic to be carried in an economical and efficient method, in recent years. These facilities, which are used to carry much higher capacities than the traditional ones, also result in the network’s vulnerability to the failure of network facilities, i.e. a single link failure. This thesis is concerned with the technology by which the spare capacity on the link of mesh networks is placed in order to protect the active traffic from network failure with a minimal cost. Although there have been many works to address the issue all of these works have been developed based on the assumption that the link cost with its capacity is linear. In fact, the linear cost functions does not reflect the reality that optic fiber cables with the specific amount of capacities are only available, in other words, the link cost function is stepwise rather than linear. Therefore, all existing algorithms developed for the linear assumption may not be applicable properly for the stepwise case. A novel heuristic algorithm is proposed to solve the problem in this thesis. The algorithm is composed of two parts as follows. In part one, a maximum flow algorithm is employed to work out the maximal amount of feasible spare paths consisting of spare capacities in the network to re-route the disrupted traffic at the event of network failure. In part two, a newly proposed algorithm is used to find an alternative path on which to place the non-rerouted traffic on the failed link with the minimum network cost increment. The superiority of the algorithm is presented over other algorithms published in this area

Manufacturing System and Supply Chain Analyses Related to Product Complexity and Sequenced Parts Delivery

Mixed model assembly has been widely used in many industries. It is applied in order to effectively deal with increasing product complexity. Sequencing and resequencing on a mixed-model assembly line is also complicated by high product complexity. To improve the performance of a mixed-model assembly system and the supply chain, one can develop efficient sequencing rules to address sequencing problems, and manage product complexity to reduce its negative impact on the production system. This research addresses aspects of sequence alteration and restoration on a mixed-model assembly line for the purpose of improving the performance of a manufacturing system and its supply chain, and addresses product complexity analysis. This dissertation is organized into Parts 1, 2, and 3 based on three submitted journal papers. Part 1. On a mixed-model assembly line, sequence alteration is generally used to intentionally change the sequence to the one desired by the downstream department; and sequence restoration is generally applied to achieve sequence compliance by restoring to the original sequence that has been unintentionally changed due to unexpected reasons such as rework. Rules and methods for sequence alteration using shuffling lines or sorting lines were developed to accommodate the sequence considerations of the downstream department. A spare units system based on queuing analysis was proposed to restore the unintentionally altered sequence in order to facilitate sequenced parts delivery. A queuing model for the repairs of defective units in the spare units system was developed to estimate the number of spare units needed in this system. Part 2. Research was conducted on product complexity analysis. Data envelopment analysis (DEA) was first applied to compare product complexity related to product variety among similar products in the same market, two DEA models including their respective illustrative models considering various product complexity factors and different comparison objectives were developed. One of these models compared the product complexity factors in conjunction with sales volume. The third DEA model was developed to identify product complexity reduction opportunities by ranking various product attributes. A further incremental economic analysis considering the changes in costs and market impact by an intended complexity change was presented in order to justify a product complexity reduction opportunity identified by the DEA model. Part 3. Two extended DEA models were developed to compare the relative complexity levels of similar products specifically in automobile manufacturing companies. Some automobile product attributes that have significant cost impact on manufacturing and the supply chain were considered as inputs in the two extended DEA models. An incremental cost estimation approach was developed to estimate the specific cost change in various categories of production activities associated with a product complexity change. A computational tool was developed to accomplish the cost estimation. In each of the above stated parts, a case study was included to demonstrate how these developed rules, models, or methods could be applied at an automobile assembly plant. These case studies showed that the methodologies developed in this research were useful for better managing mixed-model assembly and product complexity in an automobile manufacturing system and supply chain

Survivable mesh-network design & optimization to support multiple QoP service classes

Every second, vast amounts of data are transferred over communication systems around the world, and as a result, the demands on optical infrastructures are extending beyond the traditional, ring-based architecture. The range of content and services available from the Internet is increasing, and network operations are constantly under pressure to expand their optical networks in order to keep pace with the ever increasing demand for higher speed and more reliable links

Restoration network design and neural network.

by Leung Lee.Thesis (M.Sc.)--Chinese University of Hong Kong, 1992.Includes bibliographical references.Chapter SECTION 1. --- Introduction --- p.1Chapter SECTION 2. --- Formulation of Problem --- p.2Chapter 2.1 --- Problem Identification --- p.2Chapter 2.2 --- Network Planning Parameters and Assumptions --- p.3Chapter 2.3 --- Neural Network Model Transformation --- p.5Chapter 2.4 --- Algorithm and Implementation --- p.12Chapter SECTION 3. --- Simulation Results --- p.15Chapter 3.1 --- All Link Costs Are Same or Nearly the Same --- p.17Chapter 3.2 --- Fluctuated Cost in One or Two Fibre Paths --- p.18Chapter 3.3 --- Sudden Traffic Demand Change in Last Season --- p.19Chapter SECTION 4. --- Discussion --- p.20Chapter SECTION 5. --- Conclusion --- p.26GLOSSARY OF TERMS --- p.27BIBLIOGRAPHY --- p.29APPENDIX --- p.A1Chapter A --- Simulation Results --- p.A1Chapter B --- ANN Traffic Routing Example --- p.B