Knowledge discovery in hyper-heuristic using case-based reasoning on course timetabling

This paper presents a new hyper-heuristic method using Case-Based Reasoning (CBR) for solving course timetabling problems. The term Hyper-heuristics has recently been employed to refer to 'heuristics that choose heuristics' rather than heuristics that operate directly on given problems. One of the overriding motivations of hyper-heuristic methods is the attempt to develop techniques that can operate with greater generality than is currently possible. The basic idea behind this is that we maintain a case base of information about the most successful heuristics for a range of previous timetabling problems to predict the best heuristic for the new problem in hand using the previous knowledge. Knowledge discovery techniques are used to carry out the training on the CBR system to improve the system performance on the prediction. Initial results presented in this paper are good and we conclude by discussing the con-siderable promise for future work in this area.

Health, hygiene and biosecurity: tribal knowledge claims in the UK poultry industry

Since 1997 the world has been facing the threat of a human influenza pandemic that may be caused by an avian virus and the poultry industry around the globe has been grappling with the highly pathogenic strain of avian influenza H5N1, or in more informal terms bird flu. The UK poultry industry has lived with and through this threat and its consequences since 2005. This study investigates knowledge claims about health, hygiene and biosecurity as tools to ward off the threat from this virus. It takes a semi-ethnographic and discourse analytic approach to analyse a small corpus of semi-structured interviews carried out in the wake of one of the most publicised outbreaks of H5N1 in Suffolk in 2007. It reveals that claims about what best to do to protect flocks against the risk of disease are divided along lines imposed on the one hand by the structure of the industry and on the other by more 'tribal' lines drawn by knowledge and belief systems about purity and dirt, health and hygiene.

Case-Based Reasoning as a Heuristic Selector in a Hyper-Heuristic for Course Timetabling Problems

This paper studies Knowledge Discovery (KD) using Tabu Search and Hill Climbing within Case-Based Reasoning (CBR) as a hyper-heuristic method for course timetabling problems. The aim of the hyper-heuristic is to choose the best heuristic(s) for given timetabling problems according to the knowledge stored in the case base. KD in CBR is a 2-stage iterative process on both case representation and the case base. Experimental results are analysed and related research issues for future work are discussed.