Data envelopment analysis (DEA) is a nonparametric approach to estimate relative efficiency of Decision Making Units (DMUs). DEA is one of the best quantitative approaches and balanced scorecard (BSC) is one of the best qualitative methods to measure efficiency of an organization. Since simultaneous evaluation of network performance of the quad areas of BSC model is considered as a necessity an...

In international trade, exporters prefer to receive payments as quickly possible, and importers want make late possible. this respect, the payment field, an essential condition for trade transactions, also represents positions of conflict. addition, there are many cases in which various variables must be considered rather than only one specific variable representatively affecting payment, parti...

Data envelopment analysis (DEA) is a nonparametric approach to estimate relative efficiency of Decision Making Units (DMUs). DEA is one of the best quantitative approaches and balanced scorecard (BSC) is one of the best qualitative methods to measure efficiency of an organization. Since simultaneous evaluation of network performance of the quad areas of BSC model is considered as a necessity an...

This document reviews the history, development, and use of auditory weighting functions for noise impact assessment in humans and marine mammals. Advances from the modern era of electroacoustics, psychophysical studies of loudness, and other related hearing studies are reviewed with respect to the development and application of human auditory weighting functions, particularly A-weighting. The u...

The present paper investigates the choice of objective weighting schemes for computing the Purchasing Managers’ Index (PMI). To this end, the principal components variable selection strategy considered by Jolliffee (1972, 1973) is applied to monthly data of five key diffusion indexes for the period from January 1948 to October 2004, compiled by the Institute for Supply Management (ISM). It turn...

1. Abstract While various multiobjective optimization methods based on metaheuristic techniques have been proposed, these methods still encounter difficulties when handling many variables, or numerous objectives and constraints. This paper proposes a new aggregative gradient-based multiobjective optimization method for obtaining a Pareto-optimal solution set. In this method, the objective funct...