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The approaches for the parametric synthesis of the automatic control system (ACS) using the genetic algorithm that performs an approximation of Pareto-optimal solutions set are suggested. As a result, two approaches to multi-criteria optimization of ACS were considered: (1) the optimization problem was considered to be three-criteria for equally important criteria, (2) the optimization problem was...
In view of the shortcomings of the previous genetic algorithm in solving the problem of path planning of robot, this paper has improved it on the basis of the traditional genetic algorithm. The environment model is built by the grids and the fixed length serial number coding is used to encode. The random search method and the ascending order method are combined to generate the initial population....
According to the noise and overlapping characteristics of agricultural irrigation water quality monitoring data for the comprehensive evaluation may bring about the boundary fuzzy problem. This paper proposes an improved Genetic Algorithm (GA) to avoid premature convergence, the global optimal solution of the function of the Projection Pursuit (PP) function is used as the comprehensive evaluation...
The waste and trash removal management are the major challenges for cities and to perform in an optimal and efficient way is one of the field of study within Smart City. There are great challenges to overcome when the theme is waste collection. One of them is to define efficient routes in order to reduce the fuel consumption of garbage-trucks, that is the main challenge addressed in this work. The...
Course timetabiling is a process that must be done at the beginning of the education period in all educational institutions. The purpose of the timetabling is to bring together classrooms, lectures, students and lecturers at the same time without any conflicts. Course timetabiling is a difficult problem to solve when classroom constraints, teaching staff preferences, course restrictions are taken...
In this paper, we proposed a framework for detecting network's intrusions using Genetic Algorithm (GA) with multiple criteria. First of all, we build an intrusion detection system (IDS) using a pure GA with multiple selection methods. Then, we proposed one of the few hybrid algorithms in the literature, which is hybridized using a GA and a Tabu search (TS) algorithm. The proposed hybrid algorithm...
Improvements of energy efficiency and reduction of electricity consumption can be promoted by growing knowledge on the determinants of residential electricity consumption level (RECL). Due to numerousness, complexity and multiple correlations among impact factors (IFs) of RECL, feature selection is an essential step to ensure the precision and stability of an explanatory model. However, the current...
In the Team Orienteering Problem (TOP) a set of locations is given, each with a score. The objective is to determine a fixed number of routes (teams), limited in length, that visit some locations and maximize the sum of the collected scores. For the first time we introduce bi-objective TOP which has a second objective, to balance all team's scores for the purpose of obtaining fair teams. So the second...
Diabetes Mellitus is a dreadful disease characterized by increased levels of glucose in the blood, termed as the condition of hyperglycemia. As this disease is prominent among the tropical countries like India, an intense research is being carried out to deliver a machine learning model that could learn from previous patient records in order to deliver smart diagnosis. This research work aims to improve...
The paper introduces a proposal for an automated magnetic resonance (MR) image segmentation called Case-Based Genetic Algorithm Location-Dependent Image Classification (CBGA-LDIC) and presents its evaluation results. This method finds an appropriate cell set towards efficient image segmentation. It uses location-dependent image classification (LDIC), which is integrated by genetic algorithm (GA) combined...
This paper studied the optimization of the shunt release electromagnet based on Ansoft maxwell finite element simulation. The minimum size as the optimization target by taking into account the electromagnet force and temperature rise limit. In this study the electromagnetic force is calculated using finite element simulation, demand of temperature rise limit is satisfied by limiting the maximum current...
In recent years, with the high frequency of the infectious diseases outbreak, the prediction of the infectious diseases has become more and more important, so effective prediction of the infectious diseases can safeguard social stability and promote national economic prosperity. In order to improve the predictive accuracy of infectious diseases, the weight and threshold of BP neural network was optimized...
Finding an optimal configuration for the number of worker processes and executors for a Storm topology is imperative for maximizing its performance. However, this process is both tedious and time-consuming due to the vast number of parameters to tune, their intertwined relationship with each other, and the temporal overhead of simply rebalancing a topology with a new set of configuration parameters...
In this study, Vehicle Routing Problem with Time Windows (VRPTW) with known customer demands, a single depot and identical vehicles, is considered. Minimizing the total distance and the total waiting time of the vehicles are determined as objective functions for VRPTW which is capable to serve the customers in a prespecified time interval. A hybridized version of genetic algorithm which is a metaheuristic...
The paper presents a new mechanism to apply evolutionary complication of models in the previously introduced hybrid COMBI-GA sorting-out algorithm to find optimal model structure. The mechanism is based on generation of model structures using binomial random number generator with low probability and specific mutation operator. The presented experimental results demonstrate that this algorithm performs...
The article presents the use of genetic algorithm (GA) to select and classify ERD/ERS patterns. One hundred twenty eight channel EEG signal was used in the experiments. The signal was recorded for 40 people, during the process of imagining right and left hand movements. Feature extraction was performed using frequency analysis (FFT) with the resolution of 1Hz. So the features were spectral lines associated...
Aiming at the problem of optimizing the structural of X-band standing wave accelerator with multi-parameter, a method for automatic cavities structure optimized and based on genetic algorithm was proposed in this paper. In this method accelerated structure model was built with multi-parameter, using MATLAB and electromagnetic stimulation software CST to work together to optimize multi-parameter structure,...
We present a strategy to improve an evolutionary process related to a hybridization of a genetic algorithm, strongly based on local search, for the weighted tardiness and Just-in-Time scheduling problems without idle time. The presented solutions represent a schedule in identical parallel machines that are indirectly encoded in a single sequence. An empirical analysis of these features is presented,...
In this paper, an adaptive genetic algorithm based on multi-population elite selection strategy is proposed. The multi-population elite selection strategy is used to preserve the optimal individuals of each group. Finally, these optimal individuals formed a population, and then use the improved adaptive genetic algorithm to finish the solution. By comparing the simulation experiments of TSP problem...
This paper addresses the problem of Data Centers (DC) energy efficiency by proposing a proactive optimization technique to schedule the day-ahead DC operation to minimize the operational cost. The proactive optimization technique is formalized as a Mixed Integer Optimal Control Problem, known to be NP-hard. Because the time needed for solving this problem by some of the gradient-based solvers depends...
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