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This paper proposes a new solution for Traveling Salesman Problem (TSP) using genetic algorithm. A combinational crossover technique is employed in the search for optimal or near-optimal TSP solutions. It is based upon chromosomes that utilise the concept of heritable building blocks. Moreover, generation of a single offspring, rather than two, per pair of parents, allows the system to generate high...
The paper presents a novel hybrid searching COMBI GMDH-GA algorithm with GA used to discover model of optimal structure quickly because of avoiding exhaustive search. The obtained experimental results demonstrate that this algorithm performs well when solving inductive modelling tasks, both artificial and real-world.
In this paper, the optimization of planar array antenna of MIMO-SAR radar is discussed in the conditions of the array range fixed length with the minimum array spacing and the constant array elements number. As MIMO-SAR adopts sparse planar antenna, based on the principle of antenna phase center approximation, an optimization model of array considering sidelobe level and mainlobe width is set up....
The ability of a helicopter to carry externally slung loads makes it very versatile for many civil and military operations. For Helicopter slung-load system in the presence of strong disturbances and complex effects from its load, an Active Disturbance Rejection Control method(ADRC) will be applied to helicopter slung-load system and its parameter tuning based on genetic algorithm(GA) will be proposed...
Phenomenal increase in load and cost of electricity has raised many challenges ranging from security of the system to the economics of generation. For economic operation of power system, the solution to Unit Commitment problem is necessary. Unit Commitment aims to schedule the generation to meet the load demands at the most economical rate for the next few hours. It decides that which unit should...
This paper proposes a hybrid algorithm based on the genetic algorithm (GA) and the evolution strategy (ES) for the electromagnetic optimization problem. The GA is not good enough at times in searching the optimal solution from the view point of the convergence speed and the solution quality, while the ES has the risk of being trapped in a local minimum. The hybrid algorithm is composed of GA and ES...
Some of the engineering applications warrant the solution of Graph Coloring Problem. This paper investigates a new genetic procedure using divide and conquer strategy on some of the intermediate (100 ≤ n ≤ 500) and large scale benchmark graphs (n ≥ 500) to obtain the near optimal chromatic number. Finding the chromatic number is an NP-hard and combinatorial optimization problem. The divide & conquer...
Feature subset selection is an important research branch in the field of pattern recognition. Due to the traditional feature selection algorithms do not take into account the feature updating case, the paper analyzes the relationship between dataset and features, proposes a new feature activity measurement that is used to determine the influence among different features on some certain conditions...
FCM is sensitive to initialization and tends to result in local minimum in iterations. This paper studies the crossover and mutation probability of genetic algorithm and presents a new crossover and mutation probability. The proposed clustering scheme based on genetic algorithm and fuzzy c-means takes full advantage of the global optimization of genetic algorithm and the local search ability of FCM...
This paper aims at achieving global optimal solution of complex problems, such as traveling salesman problem (TSP), using extended version of real coded genetic algorithms (RCGA). Since genetic algorithm (GA) consists of several genetic operators, namely selection procedure, crossover, and mutation operators, that offers the choice to be modified in order to improve the performance for particular...
Massive job scheduling problem is an important research area in big data research era. This paper proposed self-adaptive job scheduling mechanism based on Ant-Genetic Algorithm aiming at improving convergence speed and accuracy by mutation strategy based on Ant Algorithm and efficient refinement within Genetic Algorithm. The experimental results show that the proposed algorithm can find the most suitable...
The study on the programmed cell death shows that the death of cells is controlled by genes. Based on this theory, an evolutionary algorithm is simulated by introducing control genes operators in the genetic algorithm to optima the traditional genetic algorithm. Markov chain is used to analyze the convergence of programmed cell death algorithm. It can be proved that this new algorithm can converge...
Solving puzzles based on number-sum or ordered matrices is an NP-hard problem that requires considerable computational effort. Prime examples of these are the games Sudoku and Kakuro. Kakuro relies on number sequences that must sum to a number indicator shown on the puzzle. Sudoku requires that numbers be listed in an implicit sequence in blocks and rows. Both puzzles require exclusivity of the numbers...
This paper presents a new robust methodology for solving radial distribution system reconfiguration (DSR) problem based on the concept of cooperative multi-thread strategy and hybrid meta-heuristics. The parallel cooperative meta-heuristics (PCMH) method deploys multiple concurrent explorations of the solution space using genetic algorithm (GA), particle swarm optimization (PSO) and ant colony system...
Humanoid robot motion imitation is a problem of controlling robot balance with given body motion. It is a simple method to program robot motion because many robot motion editing tools do not consider balance control. Thus, this paper proposes a concept that a RGB-D camera such as Kinect is used to capture human motion and apply the captured motion on a humanoid robot. A genetic algorithm is used to...
The regionalization problem involves aggregating several spatially contiguous basic geographical units into regions while optimizing a defined objective. Equity is one of its most important constraints with the aim to ensure the value of one or several interesting spatial attributes at a certain level and to provide solutions to specific requirements in applications. This paper tackles a new regionalization...
Cognitive Radio (CR) technology aims to reuse the underutilized frequency spectrum by creating new radio access opportunities. Cooperative spectrum sensing (CSS) is proposed to allow multiple secondary users (SUs) to scan the spectrum and verify the existence of primary user (PU). The sensing information of PU is sent by the collaborated SUs to a common fusion center to combine all the data and make...
Human-Computer Interaction gets more natural when the machine can detect human emotions faster and accurate. A lot of research is being carried out in the field of affective computing in order to improve the accuracy with speed. Bio-inspired algorithms for feature extraction and classification stages, has improved accuracy and speed further. In this paper, we propose a hybrid algorithm using CSO (Cat...
A new fuzzy c-means clustering with non-extensive entropy regularization is proposed in this paper. The purpose of entropy regularization is to form approximate solutions of singular problems in the maximum entropy framework. The non-extensive entropy with Gaussian gain is generally used for identifying non-uniform probability densities as in regular texture patterns. It is thus well suited for regularizing...
Locating nulls in the desired directions and as well as steering main beam towards the direction of interest is the most important part of the beamforming concept. Many evolutionary and metaheuristic algorithms are applied to solve these problems. In this paper a circular array is considered. Novel flower pollination algorithm is applied to position nulls with and without beam steering conditions...
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