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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...
In this paper a new method to design optimal fractional order proportional-integral-derivative (PIλDμ) controllers for time delay systems is presented. In PIλDμ controllers' parameters are composed of proportionality constant, integral constant, derivative constant, derivative order and integral order, and its design is more complex than that of conventional integer-order proportional-integral-derivative...
A novel maglev wind yaw system (MWYS) with two groups of suspension windings is proposed to replace the traditional gear-driven yaw system of horizontal-axis wind turbines. In order to overcome the power difference between these two groups of suspension windings which could affect seriously the suspension stability, the windings optimization is carried out to decrease this difference. First, the dynamic...
In this paper, a mobile robot path planning algorithm based on the rearrangement of gene is proposed for genetic algorithm and applied to solve the problem of mobile robot path planning. Firstly, it needs to build the robot path with the multi-plane model, and the genetic algorithm is used to search the optimal or sub optimal path. Then, with a new algorithm for the route of quadratic optimization,...
One of the interesting and important subjects among researchers in the field of medical and computer science is diagnosing illness by considering the features that have the most impact on recognitions. The subject discusses a new concept which is called Medical Data Mining (MDM). Indeed, data mining methods use different ways such as classification and clustering to classify diseases and their symptoms...
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...
Travelling Salesperson Problem being a classic combinatorial optimization problem is an interesting but a challenging problem to be solved. It falls under the class of NP-hard problem and becomes non-solvable for large data set by traditional methods like integer linear programming and branch and bound method, being the earlier popular approaches. Genetic Algorithm based solutions emerged as the most...
The improved algorithm based on objective layered approach is used to deal with the multi-objective network optimization problem. Based on the traditional non-dominated sorting genetic algorithm, an improved algorithm is given. In order to increase the computational efficiency, the objective layered approach is used sort the individuals of population and identify the non-inferior solution. Individuals...
The dramatically increasing energy consumption of data centers is an important issue and one of the most efficient ways to tackle the issue is through server consolidation. The basic idea of server consolidation is to move all virtual machines (VMs) to as few energy efficient servers as possible, and then switch off unused servers. Many efficient server consolidation approaches have been proposed...
This paper aims to optimize the coverage of a given area from a set of views to allow a complete mosaicing. Among the investigated methods to find the best camera positions, two of them are studied, namely the Particle Swarm Optimization (PSO) and the Genetic Algorithms (GA). After having performed experiments to compare the algorithms, the hybridization of GA and PSO is investigated. To validate...
The bin packing process can be modeled on optimization problems and it is widely studied due to its various applications. However, most implementation of the problem lacks of coordination in a unified optimization framework. Therefore, based on a general framework of multi-objective optimization with metaheuristics, jMetal, a novel genetic algorithm for bin packing problems is proposed in this paper...
The paper shows the possibility of diffraction structures designing with necessary values of the scattering characteristics at a certain sector of angles. Scattering of a plane electromagnetic wave on a complex shape metal three-dimensional structure is considered. We use a combined algorithm that includes the method of integral equation and the genetic algorithm. To determine the unknown surface...
This paper proposes a new method for the pattern synthesis of sparse concentric circular array. This method can avoid the premature and improve the poor capability of local optimization of the traditional genetic algorithm. Alternatively implementing the two kinds of genetic breeding operations can effectively alleviate the dependence of the algorithm's convergence on the choice of the initial group...
Due to the shortage of the relationship among the indicators of the system-subsystem-device level of weapon system, and the numerous following impact, operational readiness indicators transferring and spreading relationships among three levels are analyzed. The integrated allocation model of readiness indicators which can meet all the requirements, enable to lower technical and economic cost, and...
The current effects of rapid development, high population density in large residential areas and pressures on organizations to protect the environment, create a provocative framework for waste management in modern cities. The complexity of the process of garbage collection is large, and therefore a major concern for public authorities in terms of collection, transport and further processing of solid...
The paper presents a constrained optimization procedure to design a DC-DC converter with coupled inductors for minimizing the power losses. Two algorithms have been used, Genetic and Particle Swarm Optimization algorithm, and the results have been compared. In particular, with the proposed technique, the electrical, magnetic and geometrical characteristics of the coupled inductors have been obtained...
The main aim of this paper is to develop a PID tuning methodology for a processing plant using Genetic Algorithm. Genetic Algorithm or in short GA is a stochastic algorithm based on principles of natural selection and genetics. Genetic Algorithms (GAs) are a stochastic global search method that mimics the process of natural evolution. Genetic Algorithms have been shown to be capable of locating high...
Knapsack problem has been widely studied due to its broad applications in many fields of science. Dealing with imprecise data arises in many real world applications. A study report is presented to comprehend the problem and its many variants for suitable applicability. A revised method considering possibility and necessity factors to work with imprecise data and to support different levels of optimization...
This paper proposed an improvement of genetic algorithm for optimization problem. In this study, the Gaussian function is applied in crossover and mutation operators instead of traditional crossover and mutation. The algorithm is tested on five benchmark problems and compared with the self-adaptive DE algorithm, traditional differential evolution (DE) algorithm, the JDE self-adaptive algorithm and...
Considering the effects of machine breakdown and preventative maintenance (PM)on production scheduling in flowshop manufacturing cells, this paper focuses on investigating the joint optimization problem of flowshop sequence-dependent manufacturing cell scheduling and PM. A joint model is proposed and it aims to find the optimal production sequence of job families and individual jobs within each family...
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