Abstract Several clustering methods (e.g., Normalized Cut and Ratio ) divide the Min cost function by a cluster dependent factor size or degree of clusters), in order to yield more balanced partitioning. We, instead, investigate adding such regularizations original function. We first consider case where regularization term is sum squared clusters, then generalize it adaptive pairwise similariti...

Balanced growth has at least two different meanings in economics. In macroeconomics, balanced growth occurs when output and the capital stock grow at the same rate. This growth path can rationalize the long-run stability of real interest rates, but its existence requires strong assumptions. In development economics, balanced growth refers to the simultaneous, coordinated expansion of several se...

Particle swarm optimization (PSO) and differential evolution (DE) are both efficient and powerful population-based stochastic search techniques for solving optimization problems, which have been widely applied in many scientific and engineering fields. Unfortunately, both of them can easily fly into local optima and lack the ability of jumping out of local optima. A novel adaptive hybrid algori...

Energy management is one of the critical parameters in Wireless Sensor Networks. In this paper we attempt for a solution to balance the energy usage for maximizing the network lifetime, increase the packet delivery ratio and throughput. Our proposed algorithm is based on Energy Density of the clusters in Wireless Sensor Networks. The cluster head is selected using two step method and on-demand ...

Block level storage system has been widely used as it can provide users raw block device. On the basis of Orthrus system, this paper designs and implements a multiple volume servers block level storage system based on load-balanced strategy-Orthrus Plus. This system uses the dynamic load-balanced strategy based on genetic algorithm strategy to load balance the volume servers clusters and propos...

We consider a system of processor-sharing queues with state-dependent service rates. These are allocated according to balanced fairness within a polymatroid capacity set. Balanced fairness is known to be both insensitive and Pareto-efficient in such systems, which ensures that the performance metrics, when computable, will provide robust insights into the real performance of the system consider...

Cross-validation has often been applied in machine learning research for estimating the accuracies of clas-siiers. In this work, we propose an extension to this method, called distribution-balanced stratiied cross-validation (DBSCV), which improves the estimation quality by providing balanced intraclass distributions when partitioning a data set into multiple folds. We have tested DBSC V on nin...

Effective utilization of limited power resources by the sensors is pre-eminent to the Wireless Sensor Networks. Organizing the network into balanced clusters based on assigning equal number of sensors to each cluster may have the consequence of unbalanced load on the cluster heads. By-product of this is unbalanced consumption of the energy by the nodes which leads to minimization of network lif...

This paper presents a general framework for adapting any generative (model-based) clustering algorithm to provide balanced solutions, i.e., clusters of comparable sizes. Partitional, model-based clustering algorithms are viewed as an iterative two-step optimization process—iterative model re-estimation and sample re-assignment. Instead of a maximum-likelihood (ML) assignment, a balanceconstrain...

The Capacitated Vehicle Routing Problem (CVRP) is one of the most popular routing problems. In the CVRP, a fleet of capacitated vehicles located at a central depot are used to deliver products to a set of geographically dispersed customers with known demand. In this work, a new two-step approach to solve the CVRP with a heterogeneous fleet is proposed. In the first step; a balanced K-means clus...