abstractgiven the importance of the notion of efficiency in the country's economic growth, measuring the efficiency and the technology gap for various industries in order to achieve the best possible resource assignment, following the declared policy goals, is of particular importance for those countries, such as iran, which are now at the early stages of the industrialization process. hen...

Monte Carlo simulation is used to develop a flexible framework to measure the profitability, risk, and competitiveness of any insurance product. A genetic algorithm is then used to seek the optimum asset allocations that form the profitability-risk-competitiveness frontier and to examine the profitability, risk, and competitiveness trade-off's. We also show how to select the appropriate asset a...

A multiobjective programming algorithm may find multiple nondominated solutions. If these solutions are scattered more uniformly over the Pareto frontier in the objective space, they are more different choices and hence their quality is better. In this paper, we propose a quality measure called U-measure to measure the uniformity of a given set of nondominated solutions over the Pareto frontier...

today according to the competitive conditions, companies try to reduce their inventory level to diminish the costs. in companies inventory management and control should establish a balance between inventory level of spare parts, cost and the risk that arising from absence of part when is needed. it is clear that this level of spare parts inventory affected by facility characteristics and its re...

Sharp Interface Algorithm for Large Density Ratio Incompressible Multiphase Magnetohydrodynamic Flows Report Title A numerical algorithm and the corresponding paralleled implementation for the study of magnetohydrodynamics (MHD) of large density ratio, three-dimensional multiphase flows at low magnetic Reynolds numbers have been developed. The algorithm employs the method of front tracking for ...

The Factored Frontier (FF) algorithm is a simple approximate inference algorithm for Dynamic Bayesian Networks (DBNs). It is very similar to the fully factorized version of the Boyen-Koller (BK) algorithm, but in­ stead of doing an exact update at every step followed by marginalisation (projection), it always works with factored distributions. Hence it can be applied to models for which the exa...

Real life problems involve seldom only one criterion, but multiple criteria should be optimised at the same time. The criteria can even be conflicting each other, so the classical techniques used in single criteria optimization cannot be simply reused. Many ideas have been presented in the literature for addressing multiple criteria optimization problems; one of the ideas is to provide the so-c...

We present a new variant of the full (p − 1)-split algorithm, the Quadrant Shrinking Method, for finding all nondominated points of a triobjective integer program. The algorithm is easy to implement and solves at most 3|YN |+1 single-objective integer programs, where YN is the set of all nondominated points, when computing the entire nondominated frontier. A computational study demonstrates the...

This article presents an algorithm computing a border map of an image that generalizes to the n dimension graph structures used in image analysis. Such a map represents simple and multiple adjacencies, inclusion of regions, as well as the frontier type between two adjacent regions. An algorithm computing a border map, linear to the number of elements of an image, is defined in 2D, then generali...

The use of evolutionary strategies (ESs) to solve problems with multiple objectives (known as Vector Optimization Problems (VOPs)) has attracted much attention recently. Being population based approaches, ESs offer a means to find a set of Pareto-optimal solutions in a single run. Differential Evolution (DE) is an ES that was developed to handle optimization problems over continuous domains. Th...