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Where technology & law meet: Open Access research on data security & its regulation ...

Strathprints makes available Open Access scholarly outputs exploring both the technical aspects of computer security, but also the regulation of existing or emerging technologies. A research specialism of the Department of Computer & Information Sciences (CIS) is computer security. Researchers explore issues surrounding web intrusion detection techniques, malware characteristics, textual steganography and trusted systems. Digital forensics and cyber crime are also a focus.

Meanwhile, the School of Law and its Centre for Internet Law & Policy undertake studies on Internet governance. An important component of this work is consideration of privacy and data protection questions and the increasing focus on cybercrime and 'cyberterrorism'.

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Identifying preferred solutions to multi-objective binary optimisation problems, with an application to the multi-objective knapsack problem

Argyris, Nikolaos and Figueira, José Rui and Morton, Alec (2011) Identifying preferred solutions to multi-objective binary optimisation problems, with an application to the multi-objective knapsack problem. Journal of Global Optimization, 49 (2). pp. 213-235.

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Abstract

In this paper we present a new framework for identifying preferred solutions to multi-objective binary optimisation problems. We develop the necessary theory which leads to new formulations that integrate the decision space with the space of criterion weights. The advantage of this is that it allows for incorporating preferences directly within a unique binary optimisation problem which identifies efficient solutions and associated weights simultaneously. We discuss how preferences can be incorporated within the formulations and also describe how to accommodate the selection of weights when the identification of a unique solution is required. Our results can be used for designing interactive procedures for the solution of multi-objective binary optimisation problems. We describe one such procedure for the multi-objective multi-dimensional binary knapsack formulation of the portfolio selection problem.