Shuffled frog-leaping algorithm (SFLA) is a heuristic optimization technique based on swarm intelligence that is inspired by foraging behavior of the swarm of frogs. The traditional SFLA is easy to be premature convergence. So, we present an improved shuffled frog-leaping algorithm with single step search strategy and interactive learning rule(called ‘SI-SFLA’). Single step search strategy enha...

Received May 23, 2015 Revised July 13, 2015 Accepted August 2, 2015 A new distributed generation placement method based on biogeographybased optimization (BBO) is investigated in this paper. A significant novelty of this study lies in considering fuzzy load uncertainty. For this purpose a fuzzy backwardforward sweep load flow is proposed. The main objectives of this study is minimizing power lo...

The complex nature of the petrochemical industries necessitates an efficient decision on a large number of factors so as to optimally operate a plant. Production planning is an integral part of the petrochemical industry and requires the optimal selection of processes, production levels and products to maximize its profit. Previously an MILP formulation has been proposed for guiding the petroch...

In the present deregulated electricity market, power system congestion is main complication that an independent operator (ISO) faces on a regular basis. Transmission line trigger serious problems for smooth functioning in restructured causing increase cost of transmission hence affecting market efficiency. Thus, it utmost importance investigation various techniques order to relieve network. Gen...

Distributed generator (DG) placement in distribution system is one of the important tasks for better operation of distribution system. Distribution system has high r/x ratio and high operating current resulting into higher power loss and higher voltage drop. The main objective of this paper is to minimize the active power loss and to improve voltage profile of overall system by optimal sizing a...

The paper discusses yet another approach of clustering datasets whose cluster numbers are not known beforehand. The suggested approach effectively determines the number of clusters or partitions while running the algorithm. The proposed method is only limited to partitional clustering inspired from the K-means algorithm. In this work a Modified TeachingLearning-Based Optimization (MTLBO) is use...

Abstract— In our present work, we propose a nature inspired population based speech enhancement technique to find the dynamic threshold value using Teaching-Learning Based Optimization (TLBO) algorithm by using shift invariant property of dual tree complex wavelet transform (DT-CWT). The performance of these proposed methods are evaluated in terms of Perceptual Evaluation of Speech Quality (PES...

This paper provides a framework for optimization of Induction Hardening parameters by using Intelligent Techniques. Heat Treatment of Iron Alloy is carried out for improving Mechanical and Metallurgical properties like Ductility, Toughness, Hardness, and Tensile Strength etc. These properties play a important role for selection of material in Manufacturing Field. Induction Hardening on iron all...

In this study, we proposed a discrete teaching-learning-based optimisation (DTLBO) for solving the flowshop rescheduling problem. Five types of disruption events, namely machine breakdown, new job arrival, cancellation of jobs, job processing variation and job release variation, are considered simultaneously. The proposed algorithm aims to minimise two objectives, i.e., the maximal completion t...