Using harmony search for optimising university shuttle bus driver scheduling for better operational management

Managing human resource to achieve specific goal in an organisation is a crucial task. One of various aspects in managing human resource is preparing optimum scheduling to perform certain tasks. The main objective of this paper is to illustrate the preparation and the work of optimum scheduling for university shuttle bus driver using a recently develop meta-heuristic technique known as Harmony Search. A mathematical formulation for the university shuttle bus driver scheduling problem based on the requirement and the preference of the university is illustrated. The optimum schedule is generated using Harmony Search, an optimisation approach inspired by the processes in music improvisation with less mathematical computation. It can be seen that the result produced using harmony search approach to automate the optimum university shuttle bus driver scheduling is quite promising because it yield better value of objective function compared with the one being done manually. Automation of the optimum university bus driver scheduling certainly can enhanced the operational management processes. This work can be regarded as a multidisciplinary work which several domains such as computer science, mathematics, operational research and management are involved

Comparative between optimization feature selection by using classifiers algorithms on spam email

Spam mail has become a rising phenomenon in a world that has recently witnessed high growth in the volume of emails. This indicates the need to develop an effective spam filter. At the present time, Classification algorithms for text mining are used for the classification of emails. This paper provides a description and evaluation of the effectiveness of three popular classifiers using optimization feature selections, such as Genetic algorithm, Harmony search, practical swarm optimization, and simulating annealing. The research focuses on a comparison of the effect of classifiers using K-nearest Neighbor (KNN), Naïve Bayesian (NB), and Support Vector Machine (SVM) on spam classifiers (without using feature selection) also enhances the reliability of feature selection by proposing optimization feature selection to reduce number of features that are not important

Using 2-Opt based evolution strategy for travelling salesman problem

Harmony search algorithm that matches the (µ+ 1) evolution strategy, is a heuristic method simulated by the process of music improvisation. In this paper, a harmony search algorithm is directly used for the travelling salesman problem. Instead of conventional selection operators such as roulette wheel, the transformation of real number values of harmony search algorithm to order index of vertex representation and improvement of solutions are obtained by using the 2-Opt local search algorithm. Then, the obtained algorithm is tested on two different parameter groups of TSPLIB. The proposed method is compared with classical 2-Opt which randomly started at each step and best known solutions of test instances from TSPLIB. It is seen that the proposed algorithm offers valuable solutions

Reconfiguration with Simultaneous DG Installation to Improve the Voltage Profile in Distribution Network Using Harmony Search Algorithm

Due to dynamic nature of loads, total system load is more than its generation capacity that makes relieving of load on the feeders not possible and hence voltage profile of the system will not be improved to the required level. In order to meet required level of load demand, Reconfiguration & DG units are integrated in distribution network to improve voltage profile, to provide reliable and uninterrupted power supply and also to achieve economic benefits such as minimum power loss, energy efficiency and load leveling. This work proposes minimization of real power losses and improvement of voltage profile using network reconfiguration in the presence of distributed generation. Generally distributed generations (DG) are preferred with objective of minimizing real power loss and improving voltage profile in distribution system. In this work A meta heuristic Harmony Search Algorithm (HSA) is used to simultaneously reconfigure and identify the optimal locations for installation of DG units in a distribution network. Sensitivity analysis is used to identify optimal locations for installation of DG units. The proposed method has tested in MATLAB for 33-bus and 69- Bus radial distribution systems at three different load levels and the analysis is presented for loss minimization

Reconfiguration with Simultaneous DG installation to Improve the Voltage Profile in Distribution Network using Harmony Search Algorithm

Due to dynamic nature of loads, total system load is more than its generation capacity that makes relieving of load on the feeders not possible and hence voltage profile of the system will not be improved to the required level. In order to meet required level of load demand, Reconfiguration & DG units are integrated in distribution network to improve voltage profile, to provide reliable and uninterrupted power supply and also to achieve economic benefits such as minimum power loss, energy efficiency and load leveling. This work proposes minimization of real power losses and improvement of voltage profile using network reconfiguration in the presence of distributed generation. Generally distributed generations (DG) are preferred with objective of minimizing real power loss and improving voltage profile in distribution system. In this work A meta heuristic Harmony Search Algorithm (HSA) is used to simultaneously reconfigure and identify the optimal locations for installation of DG units in a distribution network. Sensitivity analysis is used to identify optimal locations for installation of DG units. The proposed method has tested in MATLAB for 33-bus and 69- Bus radial distribution systems at three different load levels and the analysis is presented for loss minimization

Analysis on Energy and Coverage Issues in Wireless Sensor Network

Two major fundamental issues in Wireless Sensor Network (WSN) are energy efficiency and coverage. Energy efficiency is the result of controlling and maintaining the energy usage. A method is considered as energy efficient if it can provide more services with the same amount of energy input, while coverage efficiency is measured by how long and how well a sensor monitors the subjected area. Hence, to obtain an energy and coverage efficiency, maximizing the coverage by reducing the energy consumption needs to be achieved. Our paper presents the potential of Derivative Harmon Search Algorithm (DHSA) in a connected WSN to achieve deployment of node that can cover optimal area and at the same time give low energy consumption

Effect of Modified Harmony Search Towards The Area Coverage In Wireless Sensor Network (WSN)

Wireless Sensor Network (WSN) have attracted many researcher to dig deeper of their abilities and specialty in carrying sensing duty. A lot of improvements have been done from day to day in many aspects including crucial issues such as energy and area coverage. Modified Harmony Search (MHS) is an improvement from basic Harmony Search (HS) method. All HS method will undergo the same step which are initialization of parameter, initialization of Harmony Memory (HM), improvisation, HM update and criterion checked. MHS undergo improvisation at the third step where the selection criteria is referring to the node placement in the memory. In this paper, we are implementing Modified Harmony Search algorithm (MHS) for node deployment purpose and the performance index such as area coverage is observed