The power supply of remote sites and applications at minimal cost and with low emissions is an important issue when discussing future energy concepts. This paper presents modeling and optimization of a photovoltaic (PV)/wind/diesel system with batteries storage for electrification to an off-grid remote area located in Rafsanjan, Iran. For this location, different hybrid systems are studied and ...

The aim of this study is to present a hybrid algorithm based on two meta-heuristic algorithms named Vibration Damping Optimization (VDO) algorithm and Genetic Algorithm (GA) for solving the stochastic capacitated location-allocation problem. For solving the model more efficiently, the simplex algorithm, stochastic simulation and the proposed hybrid algorithm are integrated to design a powerful ...

Location-Routing Problem (LRP) emerges as one of the hybrid optimization problems in distribution networks in which, total cost of the system would be reduced significantly by simultaneous optimization of locating a set of facilities among candidate locations and routing vehicles. In this paper, a mixed integer linear programming model is presented for a two-echelon location-routing problem wit...

Redundancy-allocation problem i.e. RAP is among the reliability optimization problems which make use of non-linear programming method to improve complex system. The objective this research paper through application Genetic Algorithm GA and Hybrid & Particle Swarm Optimization (H-GAPSO) on a RAP. Certain shortcomings have been seen when results are obtained by single algorithms. In order get...

Abstract Under the multi-objective framework, this paper presents a hybrid algorithm to solve robust static output feedback control problem for continuous polytopic uncertain system. To obtain static output feedback gain, a new hybrid algorithm is proposed by combination of a hybrid algorithm of the Particle Swarm Optimization (PSO) and Differential Evolution (DE), and the linear matrix inequal...

Currently, the researchers have made a lot of hybrid particle swarm algorithm in order to solve the shortcomings that the Particle Swarm Algorithms is easy to converge to local extremum, these algorithms declare that there has been better than the standard particle swarm. This study selects three kinds of representative hybrid particle swarm optimizations (differential evolution particle swarm ...

Based on MATLAB/SimEvents simulation platform and genetic algorithm, the simulation and optimization of energy consumption in hybrid flow shop is studied. Considering workshop layout and workpiece path, machining process simulation in hybrid flow shop is realized. With the processing time, processing power and stand-by power introduced into simulation model, the energy consumption simulation in...

A hybrid genetic algorithm for multiway graph partitioning is proposed. The algorithm includes an e cient local optimization heuristic. Starting at an initial solution, the heuristic iteratively improves the solution using cyclic movements of vertices. The suggested heuristic performed well in itself and as a local optimization engine in the hybrid genetic algorithm. Combined with the framework...

Bio-Inspired computing is the subset of Nature-Inspired computing. Job Shop Scheduling Problem is categorized under popular scheduling problems. In this research work, Bacterial Foraging Optimization was hybridized with Ant Colony Optimization and a new technique Hybrid Bacterial Foraging Optimization for solving Job Shop Scheduling Problem was proposed. The optimal solutions obtained by propos...