Andrew Heathcote ([email protected]) School of Medicine, The University of Tasmania Social Sciences Building, Sandy Bay, 7005, Tasmania, Australia Brandon Turner ([email protected]) Department of Psychology, The Ohio State University, Columbus, OH 43227 USA Scott D. Brown ([email protected]) School of Psychology, The University of Newcastle, Psychology Building, Universit...

In this paper, we present a multi-objective optimization approach for indoor wireless network planning subject to constraints for exposure minimization, coverage maximization and power consumption minimization. We consider heterogeneous networks consisting of WiFi Access Points (APs) and Long Term Evolution (LTE) femtocells. We propose a design framework based on Multi-objective Biogeography-ba...

We describe our development and use of DescriptiveEnvironment (DE). This is a program to aid researchers in Finite Model Theory and students of logic to automatically generate examples, counterexamples of conjectures, reductions between problems, and visualizations of structures and queries. DescriptiveEnvironment is available for free use under an ISC license at http://www.cs.umass.edu/∼immerm...

Distribution system plays an important role in supplying the electricity from generation to the consumers via transmission system. The power system is one of the most complex systems in the world. Because of the high R/X value the losses in the distribution system is more. The one of the roles of capacitor is reducing the losses in the distribution system. This paper presents an improved method...

We have compared the Y chromosomal lineage dating between sequence data and commonly used Y-SNP plus Y-STR data. The coalescent times estimated using evolutionary Y-STR mutation rates correspond best with sequence-based dating when the lineages include the most ancient haplogroup A individuals. However, the times using slow mutated STR markers with genealogical rates fit well with sequence-base...

We propose a differential evolution (DE) algorithm for the calculation of the interval and fuzzy variance. In particular, we see that the DE methods can be efficient for the fuzzy variance of a relatively high number of fuzzy data; computational results with up to 100 data show that the number of function evaluations to obtain the estimated global solutions grows less then quadratically with th...

The task of global optimization is to find a point where the objective function obtains its most extreme value. Differential evolution (DE) is a population-based heuristic approach that creates new candidate solutions by combining several points of the same population. The algorithm has three parameters: amplification factor of the differential variation, crossover control parameter and populat...

Differential evolution (DE) has become a popular and promising technique in the recent decade. There are many successful applications implemented DE in scientific and engineering fields. However, we rarely found it applying to the field of highly constrained aggregate production planning (APP) problems. Besides, in the course of solving the APP problem, we discover that the most often used DE s...

Diverse sustainable supplier selection (SSS) methodologies have been suggested by the practitioners in earlier, to find a solution to the SSS problem. A SSS problem fundamentally is a multi-criteria practice. It is a judgment of tactical significance to enterprises. The nature of this decision usually is difficult and unstructured. Optimization practices might be useful tools for these types of...

Abstract In this paper we present experimental results to show deep view on how selfadaptive mechanism works in differential evolution algorithm. The results of the self-adaptive differential evolution algorithm were evaluated on the set of 24 benchmark functions provided for the CEC2006 special session on constrained real parameter optimization. In this paper we especially focus on how the con...