Healthcare analytics provide many benefits in healthcare dashboard systems. datasets majorly contains categorical attributes. This paper proposed an optimized clustering for dataset named harmony search based (HSCC). The existing k-modes algorithm is one of the well-known data-clustering algorithm. Since produces local optimal clusters. Generally, researchers use genetic (GA) algorithms to conv...

In this paper a model is proposed for distribution centers location and joint replenishment of a distribution system that is responsible for orders and product delivery to distribution centers. This distribution centers are under limitedwarehouse space and this can determine amount of requirement product by considering proposed discount.The proposed model is develop to minimize total costs cons...

This paper discusses the optimal node placement problem of Industrial Wireless Sensor Networks (IWSNs). Compared with the non-industrial Wireless Sensor Networks (WSNs), IWSNs have a critical requirement on the reliability of networks. Thus, a new model of the IWSNs node placement is formulated in which the reliability, cost, load constraint and scalability are taken into account. Considering i...

This chapter presents a novel Harmony Search (HS) algorithm used to solve security constrained optimal power flow (OPF) with various generator fuel cost characteristics. HS is a recently developed derivative-free, meta-heuristic optimization algorithm, which draws inspiration from the musical process of searching for a perfect state of harmony. This chapter analyses the evolution of the populat...

Many wireless sensor network applications require K-coverage of the monitored area. In this paper, we propose a scalable harmony search based algorithm in terms of execution time, K-Coverage Enhancement Algorithm (KCEA), it attempts to enhance initial coverage, and achieve the required K-coverage degree for a specific application efficiently. Simulation results show that the proposed algorithm ...

Dynamic optimization problems present great challenges to the research community because their parameters are either revealed or changed during the course of an ongoing optimization process. These problems are more challenging than static problems in real-world applications because the latter are usually dynamic, with the environment constantly subjected to change or the size of a problem incre...