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Adaptive automated construction of hybrid heuristics for exam timetabling and graph colouring problems

<22> This paper presents the first extensive statistical analysis on automated heuristic hybridization. A fundamentally general hybridization of widely-used heuristics is proposed. Instead of developing `yet another technique' for specific problems, we seek a general integration of heuristics based on a deeper understanding of the integration, and facilitate more robust search methodologies for a wider range of problems. This general methodology has been quickly adapted within and beyond the specific problem domains, and the work is in the top 10% of cited papers in Computer Science in ISI Essential Science Indicators. The journal has a 5-year impact factor of 2.524.