Nowadays, the subject of vision metrology network design is local enhancement of the existing network. In the other words, it has changed from first to third order design concept. To improve the network, locally, some new camera stations should be added to the network in drawback areas. The accuracy of weak points is enhanced by the new images, if the related vision constraints are satisfied si...

in this paper, we proposed an algorithm for solving the problem of task scheduling using particle swarm optimization algorithm, with changes in the selection and removing the guide and also using the technique to get away from the bad, to move away from local extreme and diversity. scheduling algorithms play an important role in grid computing, parallel tasks scheduling and sending them to appr...

This paper presents a new strategy that can solve the Grid task scheduling problem with multiple objectives (NP-Hard) in polynomial time using evolutionary algorithms. The results obtained by our proposed algorithm were compared and evaluated against the -constraints classic Multi-Objective Optimization method, which uses the deterministic algorithm of Branch and Bound to find the real Pareto f...

arguably, the natural gas transmission pipeline infrastructure in iran represents one of the largest andmost complex mechanical systems in the world. the optimization of large gas trunk lines known asigat results in reduced fuel consumption or higher capability and improves pipeline operation. in thecurrent study, a single-objective optimization was conducted for khormoj compressor station on t...

In this study, a multiobjective optimization is applied to Optimal Power Flow Problem (OPF). To effectively achieve this goal, a Multiobjective Ant Lion algorithm (MOALO) is proposed to find the Pareto optimal front for the multiobjective OPF. The aim of this work is to reach good solutions of Active and Reactive OPF problem by optimizing 4-conflicting objective functions simultaneously. Here a...

In the past few years, multi-objective optimization (MOO) algorithms have been extensively applied in several fields including engineering design problems. A major reason is the advancement of evolutionary multi-objective optimization (EMO) algorithms that are able to find a set of non-dominated points spread on the respective Pareto-optimal front in a single simulation. Besides just finding a ...

This paper deals with multi-objective optimization in gait planning of a 7-dof biped robot ascending and descending some staircases. Both its power consumption as well as dynamic balance margin depends on a few common design parameters. The biped robot should have a maximum dynamic balance margin but at the expense of minimum power. Thus, a conflicting relationship exists between these two obje...

in financial matters, portfolio can be interpreted as a combination or a series of investments hold by an institution or a person. portfolio optimization is one of the most important concerns of investors for maximizing the portfolio in financial markets. the formation of portfolio is a vital and critical decision for the companies.  in fact, the selection of portfolio is to specify the capital...

We present results from a study comparing a recently developed coevolutionary genetic algorithm (CGA) against a set of evolutionary algorithms using a suite of multiobjective optimization benchmarks. The CGA embodies competitive coevolution and employs a simple, straightforward target population representation and fitness calculation based on developmental theory of learning. Because of these p...

The following MOEA algorithms are briefly summarized and compared: • NPGA Niched Pareto Genetic Algorithm (1994) – NPGA II (2001) • NSGA Non-dominated Sorting Genetic Algorithm (1994) – NSGA II (2000) • SPEA Strength Pareto Evolutionary Algorithm (1998) – SPEA2 (2001) – SPEA2+ (2004) – ISPEA Immunity SPEA (2003) • PAES Pareto Archived Evolution Strategy (2000) – M-PAES Mimetic PAES (2000) • PES...