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The ant system is a new meta-heuristic for hard combinatorial optimization problems. It is a population-based approach that uses exploitation of positive feedback as well as greedy search. It was first proposed for tackling the well known Traveling Salesman Problem (TSP), but has been also successfully applied to problems such as quadratic assignment, job-shop scheduling, vehicle routing and graph coloring.In this paper we introduce a new rank based version of the ant system and present results of a computational study, where we compare the ant system with simulated annealing and a genetic algorithm on several TSP instances. It turns out that our rank based ant system can compete with the other methods in terms of average behavior, and shows even better worst case behavior. (author's abstract) / Series: Working Papers SFB "Adaptive Information Systems and Modelling in Economics and Management Science"

Phylogenetic diversity (PD) is a measure of species biodiversity quantified by how much of an evolutionary tree is spanned by a subset of species. In this thesis, we study optimization problems that aim to find species sets with maximum PD in different scenarios, and examine random extinction models under various assumptions to predict the PD of species that will still be present in the future. Optimizing PD with Dependencies is a combinatorial optimization problem in which species form an ecological network. Here, we are interested in selecting species sets of a given size that are ecologically viable and that maximize PD. The NP-hardness of this problem is proved and it is established which special cases of the problem are computationally easy and which are computationally hard. It is also shown that it is NP-complete to decide whether the feasible solution obtained by the greedy algorithm is optimal. We formulate the optimization problem as an integer linear program and find exact solutions to the largest food web currently in the empirical literature. In addition, we give a generalization of PD that can be used for example when we do not know the true evolutionary history. Based on this measure, an optimization problem is formulated. We discuss the complexity and the approximability properties of this problem. In the generalized field of bullets model (g-FOB), species are assumed to become extinct with possibly different probabilities, and extinction events are independent. We show that under this model the distribution of future phylogenetic diversity converges to a normal distribution as the number of species grows. When extinction probabilities are influenced by some binary character on the tree, the state-based field of bullets model (s-FOB) represents a more realistic picture. We compare the expected loss of PD under this model to that under the associated g-FOB model and find that the former is always greater than or equal to the latter. It is natural to further generalize the s-FOB model to allow more than one binary character to affect the extinction probabilities. The expected future PD obtained for the resulting trait-dependent field of bullets model (t-FOB) is compared to that for the associated g-FOB model and our previous result is generalized.

Bibliography: leaves 125-131. / xi, 131 leaves : ill. ; 30 cm. / Title page, contents and abstract only. The complete thesis in print form is available from the University Library. / This thesis examines the performace of optimisation networks. The main objectives are to determine if there exist any factors which limit the solution quality that may be achieved with optimisation networks, to determine the reasons for any such limitations and to suggest remedies for them. / Thesis (Ph.D.)--University of Adelaide, Dept. of Electrical and Electronic Engineering, 1996

Thesis (Ph. D.)--University of Washington, 2007. / Includes bibliographical references (p. 134-142).

Thesis (Ph.D.)--University of Tulsa, 1995. / Includes bibliographical references (leaves 118-121).

Thesis (MSc) - Information and Communication Technology, Swinburne University of Technology, 2007. / Submitted in partial fulfilment of the requirements for the degree of Master of Science (IT), [Information and Communication Technology], Swinburne University of Technology - 2007. Typescript. Includes bibliographical references.

Thesis (M.App.Sc.) - Carleton University, 2005. / Includes bibliographical references (p. 99-101). Also available in electronic format on the Internet.

Thesis (Ph. D.)--University of Pittsburgh, 1993. / eContent provider-neutral record in process. Description based on print version record. Includes bibliography (leaves 216-226).

Thesis (Ph. D.)--University of Texas at Austin, 2003. / Vita. Includes bibliographical references. Available also from UMI Company.