This paper presents an proportional integral (PI) based voltage-reactive power control for wind diesel based decentralized hybrid power system with wide range of disturbances to demonstrate the compensation effect on system with intelligent tuning methods such as genetic algorithm (GA), artificial neural network (ANN) and adaptive neuro fuzzy inference system (ANFIS). The effect of probabilisti...

In this paper, a new Genetic Algorithm (GA) based methodology is proposed to optimize the Degree of Hybridization (DOH) in a passenger parallel hybrid car. At first step, target parameters for the vehicle are decided and then using ADvanced VehIcle SimulatOR (ADVISOR) software, the variation pattern of these target parameters, across the different DOHs, is extracted. At the next step, a suitabl...

Flexible job-shop scheduling problem (FJSP) has been well known as one of the most difficult NP-hard combinatorial optimization problems. This problem FJSP is an extension of job-shop scheduling problem (JSP) which is to create a sequence of operations satisfying the precedence relationship together with assignment of time and resources for each operation. Thus, the FJSP model is closer to the ...

In this paper, a simplified model with a lower order is first developed for a nuclear steam generator system and verified against some realistic environments. Based on this simplified model, a hybrid multi-input and multi-out (MrMO) control system, consisting of feedforward control (FFC) and feedback control (FBC), is designed for wide range conditions by using the genetic algorithm (GA) techni...

A Genetic Algorithm (GA) is developed to nd small or minimal Fixed Polarity Reed-Muller expressions (FPRMs) for large functions. We combine the GA with greedy heuristics, i.e. we use Hybrid GAs (HGAs). We show by experiments that results superior to all other approaches for large functions can be obtained using GAs.

We proposed the concept dynamic traveling salesman problem (Dynamic TSP). According to the characteristics of Dynamic TSP, we used a hybrid algorithm of n-OPT and GA to solve it. 2-OPT and 3-OPT are used in GA procedures of mutation and selection. The productivity and quality of solutions under dynamic conditions are evaluated by the experiment.

In consideration of capacity constraints, fuzzy defect ratio, and fuzzy transport loss ratio, this paper attempted to establish an optimized decision model for production planning and distribution of a multiphase, multiproduct reverse supply chain, which addresses defects returned to original manufacturers, and in addition, develops hybrid algorithms such as Particle Swarm Optimization-Genetic ...

Abstract—In real world applications, optimization is an inevitable stage in any engineering design. In recent days the optimization theory is also fused into other sciences which require precision in its final result. This topic sounds like a promising domain for research almost in all areas of science and technology. Perhaps several solution methods are proposed for solving problems that requi...

Accurate and timely weather forecasting is a major challenge for the scientific community in hydrological research such as river training works and design of flood warning systems. Neural Network (NN) is a popular regression method in rainfall predictive modeling. This paper investigates the effectiveness of the hybrid Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) evolved neural ...

This paper presents a hybrid of genetic algorithm (GA) and local search operators for solving the three-matching problem (3MP). Several general / heuristic crossover and local hill-climbing operators are introduced. The adaptive process based on the observation of on-line performance of GA is used to select the feasible operators. In particular, the probability of applying an operator is increa...