The distributed genetic algorithm (DGA) is applied for loading pattern optimization problems of the pressurized water reactors. A basic concept of DGA follows that of the conventional genetic algorithm (GA). However, DGA equally distributes candidates of solutions (i.e. loading patterns) to several independent “islands” and evolves them in each island. Communications between islands, i.e. migra...

Genetic algorithms (GAs) are optimization tools that simulate evolutionary processes in order to develop solutions for a wide range of optimization problems. In recent years, they have increasingly gained acceptance in industry, as confidence improves in their abilities to solve complex problems that have previously appeared to be unsolvable. One example of an industrial application for GAs is ...

due to project evaluation complexity and resource constraints, the project portfolio optimization is numerous decision making challenges. hence, many researches have been done to introduce model and methods for portfolio optimization. but most of them have not considered the interaction between projects. considering the interactions between projects increase complexity of portfolio optimization...

In this paper proposes a fuzzy multi-objective hybrid Genetic and Bee colony optimization algorithm(GA-BCO) to find the optimal restoration of loads of power distribution network under fault.Restoration of distribution systems is a complex combinatorial optimization problem that should beefficiently restored in reasonable time. To improve the efficiency of restoration and facilitate theactivity...

We propose the use of a hierarchical Genetic Algorithm (GA) for optimization in complex landscapes. While the slave GA tries to find local optima in the restricted fitness landscape of low complexity, the master GA tries to identify interesting regions in the entire landscape. The slave GA is a conventional GA with high convergence. The master GA is more exploratory in nature. This GA clusters ...

among the several non-conventional processes, electrical discharge machining (edm) is the most widely and successfully applied for the machining of conductive parts. in this technique, the tool has no mechanical contact with the work piece and also the hardness of work piece has no effect on the machining pace. hence, this technique could be employed to machine hard materials such as super allo...

With the formation of the competitive electricity markets in the world, optimization of bidding strategies has become one of the main discussions in studies related to market designing. Market design is challenged by multiple objectives that need to be satisfied. The solution of those multi-objective problems is searched often over the combined strategy space, and thus requires the simultaneous...

Heuristic optimization provides a robust and efficient approach for solving complex real-world problems. The focus of this research is on a hybrid method combining two heuristic optimization techniques, genetic algorithms (GA) and particle swarm optimization (PSO), for the global optimization of multimodal functions. Denoted as GA-PSO, this hybrid technique incorporates concepts from GA and PSO...

This paper deals with the application of multi-agent system concept for optimization of dynamic uncertain process. These problems are known to have a computationally demanding objective function, which could turn to be infeasible when large problems are considered. Therefore, fast approximations to the objective function are required. This paper employs bundle of intelligent systems algorithms ...

vendor managed inventory is a continuous replenishment program that is designed to provide major cost saving benefits for both vendors and retailers. previous research on this area mainly included single objective optimization models where the objective is to minimize the total supply chain costs or to maximize the total supply chain benefits. this paper presents a bi-objective mathematical mod...