Abstract: The construction industry and housing subsector are fraught with risks that have the potential of negatively impacting on the achievement of project objectives. The success or otherwise of most construction projects depends to large extent on how well these risks have been managed. The recent paradigm shift by the subsector to use of formal risk management approach in contrast to hitherto developed rules of thumb means that risks must not only be identified but also properly assessed and responded to in a systematic manner. The study focused on identifying risks associated with housing development projects and prioritisation assessment of the identified risks in order to provide basis for informed decision. The study used a three-step identification framework: review of literature for similar projects, expert consultation and questionnaire based survey to identify potential risk factors. Delphi survey method was employed in carrying out the relative prioritization assessment of the risks factors using computer-based Analytical Hierarchical Process (AHP) software. The results show that 19 out of the 50 risks significantly impact on housing development projects. The study concludes that although significant numbers of risk factors have been identified as having relevance and impacting to housing construction projects, economic risk group and, in particular, ‘changes in demand for houses’ is prioritised by most developers as posing a threat to the achievement of their housing development objectives. Unless these risks are carefully managed, their effects will continue to impede success in these projects. The study recommends the adoption and use of the combination of multi-technique identification framework and AHP prioritization assessment methodology as a suitable model for the assessment of risks in housing development projects.
Abstract: This article proposes a hybrid algorithm for spectrum
allocation in cognitive radio networks based on the algorithms
Analytical Hierarchical Process (AHP) and Technique for Order of
Preference by Similarity to Ideal Solution (TOPSIS) to improve the
performance of the spectrum mobility of secondary users in cognitive
radio networks. To calculate the level of performance of the proposed algorithm a
comparative analysis between the proposed AHP-TOPSIS, Grey
Relational Analysis (GRA) and Multiplicative Exponent Weighting
(MEW) algorithm is performed. Four evaluation metrics are used.
These metrics are accumulative average of failed handoffs,
accumulative average of handoffs performed, accumulative average
of transmission bandwidth, and accumulative average of the
transmission delay. The results of the comparison show that AHP-TOPSIS Algorithm
provides 2.4 times better performance compared to a GRA Algorithm
and, 1.5 times better than the MEW Algorithm.