Placement process is one of the vital stages in physical design. In this stage, modules and elements of circuit are placed in distinct locations according to optimization basis. So that, each placement process tries to influence on one or more optimization factor. In the other hand, it can be told unequivocally that FPGA is one of the most important and applicable devices in our electronic worl...

SCADA is an essential system to control critical facilities in big cities. SCADA is utilized in several sectors such as water resource management, power plants, electricity distribution centers, traffic control centers, and gas deputy. The failure of SCADA results in crisis. Hence, the design of SCADA system in order to serve a high reliability considering limited budget and other constraints i...

Efficient portfolio design is a principal challenge in modern computational finance. Optimization based on Markowitz two-objective mean-variance approach is computationally expensive for real financial world. Practical portfolio design introduces further complexity as it requires the optimization of multiple return and risk measures. Some of these measures are nonlinear and nonconvex. The probl...

Financial health of many organizations now-a-days is being affected by investment in software and their cost estimation. Therefore, to provide effective cost estimation models are the most complex activity in software engineering fields. This paper presents a fuzzy clustering and optimization model for software cost estimation. The proposed model uses Pearson product-moment correlation coeffici...

Abstract—A Particle Swarm optimized Fuzzy Logic Congestion Detection (FLCD) was recently proposed for best-effort service networks. This algorithm synergically combines the good characteristics of traditional Active Queue Management (AQM) algorithms and fuzzy logic based AQM algorithms. Its membership functions are designed automatically by using a Multi-objective Particle Swarm Optimization (M...

In multiobjective particle swarm optimization (MOPSO), the global-best is randomly selected for each population from a nondominated solution set. However, this Roulette wheel-based global selection ineffective convergence and diversity when problem has numerous decision variables or large number of candidates. Thus, study proposes cluster-based MOPSO (CMOPSO). CMOPSO, similarities between parti...

In this paper, the influence of -dominance on Multi-objective Particle Swarm Optimization (MOPSO) methods is studied. The most important role of dominance is to bound the number of non-dominated solutions stored in the archive (archive size), which has influences on computational time, convergence and diversity of solutions. Here, -dominance is compared with the existing clustering technique fo...

In this paper, we describe a systematic multi-objective problem solving approach, simulataneosly minimizing two conflicting goals average surface roughness ‘Ra’ and build time ‘T ’, for object manufacturing in FDM process by usage of evolutionary algorithms. Popularly used multi-objective genetic algorithm NSGA-II and recently proposed multi-objective particle swarm optimization (MOPSO) algorit...

this paper proposes per unit coding for combined economic emission load dispatch problem. in the proposed coding, it is possible to apply the percent effects of elements in any number and with high accuracy in objective function. in the proposed per unit coding, each function is transformed into per unit form based on its own maximum value and has a value from 0 to 1. in this paper, particle sw...

Task scheduling is a crucial issue in distributed (disbursed) heterogeneous processing environment and significantly influence the performance of the system. The task scheduling problem has been identified to be NP-complete in its universal frame. In this paper the task scheduling problem is investigated using multiple-objective particle (molecule) swarm optimization algorithm with crowded disp...