Efficient optimisation of structures using tabu search

This paper presents a novel approach to the optimisation of structures using a Tabu search (TS) method. TS is a metaheuristic which is used to guide local search methods towards a globally optimal solution by using flexible memory cycles of differing time spans. Results are presented for the well established ten bar truss problem and compared to results published in the literature. In the first example a truss is optimised to minimise mass and the results compared to results obtained using an alternative TS implementation. In the second example, the problem has multiple objectives that are compounded into a single objective function value using game theory. In general the results demonstrate that the TS method is capable of solving structural optimisation problems at least as efficiently as other numerical optimisation approaches

Local search: A guide for the information retrieval practitioner

There are a number of combinatorial optimisation problems in information retrieval in which the use of local search methods are worthwhile. The purpose of this paper is to show how local search can be used to solve some well known tasks in information retrieval (IR), how previous research in the field is piecemeal, bereft of a structure and methodologically flawed, and to suggest more rigorous ways of applying local search methods to solve IR problems. We provide a query based taxonomy for analysing the use of local search in IR tasks and an overview of issues such as fitness functions, statistical significance and test collections when conducting experiments on combinatorial optimisation problems. The paper gives a guide on the pitfalls and problems for IR practitioners who wish to use local search to solve their research issues, and gives practical advice on the use of such methods. The query based taxonomy is a novel structure which can be used by the IR practitioner in order to examine the use of local search in IR

Toward an automaton Constraint for Local Search

We explore the idea of using finite automata to implement new constraints for local search (this is already a successful technique in constraint-based global search). We show how it is possible to maintain incrementally the violations of a constraint and its decision variables from an automaton that describes a ground checker for that constraint. We establish the practicality of our approach idea on real-life personnel rostering problems, and show that it is competitive with the approach of [Pralong, 2007]

Satellite downlink scheduling problem: A case study

The synthetic aperture radar (SAR) technology enables satellites to efficiently acquire high quality images of the Earth surface. This generates significant communication traffic from the satellite to the ground stations, and, thus, image downlinking often becomes the bottleneck in the efficiency of the whole system. In this paper we address the downlink scheduling problem for Canada's Earth observing SAR satellite, RADARSAT-2. Being an applied problem, downlink scheduling is characterised with a number of constraints that make it difficult not only to optimise the schedule but even to produce a feasible solution. We propose a fast schedule generation procedure that abstracts the problem specific constraints and provides a simple interface to optimisation algorithms. By comparing empirically several standard meta-heuristics applied to the problem, we select the most suitable one and show that it is clearly superior to the approach currently in use.Comment: 23 page

A bi-objective hub-and-spoke approach for reconfiguring Web communities

Web communities in general grow naturally, thus creating unbalanced network structures where a few domains centralise most of the linkups. When one of them breaks down, a significant part of the community might be unable to communicate with the remaining domains. Such a situation is highly inconvenient, as in the case of wishing to pursue distribution policies within the community, or for marketing purposes. In order to reduce the damages of such an occurrence, the Web community should be reconfigured, in such a way that a complete sub-network of main domains -the hubs - is identified and that each of the other domains of the community - the spokes - is doubly linked at least with a hub. This problem can be modellised through a bi-objective optimisation problem, the Web Community Reconfiguring Problem, which will be presented in this paper. A bi-objective mixed binary formulation will also be shown, along with a brief description of GRASP, tabu search and hybrid heuristics which were developed to find feasible solutions to the problem, possibly efficient solutions to the bi-objective problem. A computational experiment is reported, involving comparison of these metaheuristics when applied to several Web communities, obtained by crawling the Web and using epistemic boundaries and to other randomly generated ones. The heuristics revealed excellent quality for the small dimension cases whose efficient solutions were roughly all determined. As for the other medium and higher dimension instances, the heuristics were successful in building a wide variety of feasible solutions that are candidate efficient solutions. The best behaviour was attained with the GRASP and the GRASP and tabu hybrid search. Comparison of some metrics before and after reconfiguration confirmed that the final structures are more balanced in terms of degree distribution reinforcing the connecting effect imposed by the reconfiguration process