The growing dominance in terms of industrial applications has helped polymer-based composite materials conquering new markets relentlessly. But the presence fibrous residuals and abrasive particles as reinforcement polymer matrix composites (PMCs) affects output quality characteristics (OQCs) microdrilling operations. OQC aims at reducing overcuts momentous material removal rate (MRR). In such ...

In this paper, an innovative method for designing the top load of a very low frequency (VLF) thirteen-tower umbrella antenna based on multiobjective particle swarm optimization (MOPSO) is proposed. The design antenna’s mainly involves sag and position distribution cables. On basis analyzing influence cables’ radiation efficiency, MOPSO Pareto optimality used to optimize location catenaries. res...

The aim os this paper is to study the hybridization of two multi-objective algorithms in the context of a real problem, the MANETs problem. The algorithms studied are Particle Swarm Optimization (MOPSO) and a new multiobjective algorithm based in the combination of NSGA-II with Evolution Strategies (ESN). This work analyzes the improvement produced by hybridization over the Pareto’s fronts comp...

This paper focuses on solving a typical multi-mode resource leveling problem, in which activity duration depends on committed resources, project deadlines and other constraints. To solve this problem, we establish a multi-objective model to minimize project duration, resource requirements and resource variance. Based on the established model, a novel Elitist Vector Evaluated Particle Swarm Opti...

Existing approaches for optimal planning of Wireless Mesh Networks (WMNs) deployment revolves around the deployment cost as the pivotal concept to optimize. In this paper, we adopt a new approach to optimize the planning of WMNs that guarantees an acceptable level of network performance prior to its deployment. It is a simultaneous optimization process of network deployment cost and network thr...

this article presents the application of two algorithms: heuristic big bang-big crunch (hbb-bc) and a heuristic particle swarm ant colony optimization (hpsaco) to discrete optimization of reinforced concrete planar frames subject to combinations of gravity and lateral loads based on aci 318-08 code. the objective function is the total cost of the frame which includes the cost of concrete, formw...

Proteins interact with each other in a highly specific manner, and protein interactions play a key role in many cellular processes. Since protein interactions determine the outcome of most cellular processes, so identifying and characterizing Protein– Protein interactions and their networks are essential for understanding the mechanisms of biological processes on a molecular level. This paper e...

The purpose of this study is to optimize the stock price forecasting model with meta-innovation method in pharmaceutical companies.In this research, stock portfolio optimization has been done in two separate phases.The first phase is related to forecasting stock futures based on past stock information, which is forecasting the stock price using artificial neural network.The neural network used ...