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Knowledge discovery from data demands that it shall be the data themselves that reveal the groups (i.e. the data elements in each group) and the number of groups. For the ubiquitous task of clustering, K-MEANS is the most used algorithm applied in a broad range of areas to identify groups where intra-group distances are much smaller than inter-group distances. As a representative-based clustering approach, K-MEANS offers an extremely efficient gradient descent approach to the total squared error of representation; however, it not only demands the parameter k, but it also makes assumptions about the similarity of density among the clusters. Therefore, it is profoundly affected by noise. Perhaps more seriously, it can often be attracted to local optima despite its immersion in a multi-start scheme. We present an effective genetic algorithm that combines the capacity of genetic operators to conglomerate different solutions of the search space with the exploitation of the hill-climber. We advance a previous genetic-searching approach called GENCLUST, with the intervention of fast hill-climbing cycles of K-MEANS and obtain an algorithm that is faster than its predecessor and achieves clustering results of higher quality. We demonstrate this across a series of 18 commonly researched datasets.

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PurposeMany road authorities considered contracting out road maintenance to the private sector based on performance measures as an alternative and better solution than traditional methods of contracting. It highlights issues of interest to road authorities in the context of saving maintenance costs and managing contracting times effectively. This method is named as performance based maintenance by contracting (PBMC) and has substantial success records in minimizing infrastructure maintenance costs in many developed and developing countries over the last two decades. It has received the attention of researchers and practitioners. However, the literature on PBMC is reasonably high although the concept of PBMC is relatively new. The purpose of this paper is to carry out a comprehensive state of the art review of the literature that has been conducted in the recent years.Design/methodology/approachA total of 62 published report and journal articles related to performance based maintenance by contracting for road network system has been analysed and reviewed in this paper.FindingsThis paper analyses the literature on PBMC and presents examples of developed and developing countries that have been successfully maintaining their road network systems using PBMC as their preferred method of contracting.Practical implicationsThe potential of reducing maintenance costs, increasing the quality of works and reducing the chance of corruption in the long run in developing countries are the challenging issues for PBMC, which needs more attention. This paper can be used as a base or platform for future research in the area of PBMC such as developing optimal policies and cost models.Originality/valueThis paper would be useful for the research on PBMC. It would be beneficial for the engineers or professionals in improving the performance of road maintenance and management.