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The Distributed Generation (DG) systems of today face a multitude of problems, among which the pollutant emissions and the energy efficiency play a key role. In this sense, the study of optimal operation strategies for such systems becomes highly important. Thus, the purpose of this work will be to investigate using the Nondominated Sorting Genetic Algorithm II (NSGA II) the operation of a 4 gas microturbine...
This paper presents the stages for solving fuzzy multi-objective optimization problems using genetic algorithm approach. Before applying non-dominated sorting genetic algorithm II (NSGA II) techniques to obtain optimal solution, first multi-objective possibilistic (fuzzy) programming was converted into an equivalent auxiliary crisp model to form deterministic programming model. To determine the best...
An island partitioning method based on cloud adaptive genetic algorithm is proposed. The traditional genetic algorithm is modified by making use of the trait of cloud theory, which shows both randomness and a tendency of stability. The traditional crossover operator is replaced by cloud crossover operator, aiming at improving global searching ability and avoiding falling into local minimums. The concept...
The solution of plant-level optimal load dispatch can effectively improve the economic benefits of the plant. It not only response to the national energy conservation and the strategic needs of sustainable development but also adapt to the electricity's market-oriented reform called “separating form and bidding on power net”. To increase the economic benefits, it is significant for the thermal power...
In this paper it presents a methodology that aims to deliver a near optimal Distributed Generation (DG) in the process of allocation DG units by using a hybrid genetic algorithm, Hence, the main aim is to minimize power losses in DG. The proposed algorithm in this paper involves two main parts of algorithms an artificial neural network (ANN) that found to evaluate the fitness function in the generation...
The major challenge in the design of Interval type-2 fuzzy logic system (IT2FLS) is to determine the optimal parameters for their antecedent and consequent parts. The most frequently used objective function for the design of IT2FLSs is root mean squared error (RMSE). However, other than RMSE, the maximum absolute error (MAE) for each of identification samples is very important. This paper propose...
In this paper a prototype of crude network tanks system is modeled from the first principle, the system is then controlled using the PID (Proportional Integral Derivative) control system, the PID tuning parameters are optimized successfully using Genetic algorithm based on control performance indices (i.e. Mean Square Error (MSE), integral square error (ISE), integral absolute error (IAE), and integrated...
Over the years the science has developed rapidly. And the Optimization science also has been developed to solve the difficult problems. Now the optimization science is the tendency to solve several problems by applying algorithms and optimization methods (Meta heuristics Algorithms). In the previous decades, the researchers have worked and solved their problems with limited optimization methods (deterministic...
Problem of community detection has attracted many research efforts in recent years. Most of the algorithms developed for this purpose, take advantage of single-objective optimization methods which may be ineffective for complex networks. In addition, most of the networks in the real world are weighted, and therefore, this fact must be of special interest in order to achieve more precise communities...
In this paper, a new approach for placement of both Distributed Generation (DG) units and capacitor banks in distribution systems is proposed. The goal is to 1) reduce the total real and reactive power losses, 2) improve the voltage profile, and 3) improve the power factor for the total demand. The method uses a bus-ranking scheme based on a weighted sum of indices representative of the impacts that...
In LTE, tracking Areas (TAs) are used to group cells where each cell is assigned to one TA and each user equipment (UE) registers with one TA. A TA may be connected to more than one mobility management entity (MME), which records the current TAs of its UEs. The home subscriber server (HSS) records the current MME for each UE. When a UE moves to a new TA, a TA update procedure is triggered to update...
This paper discusses a new approach to optimize overcurrent relay coordination in power distribution system by using a genetic algorithm. A modified objective function with constraints is taken to solve the relay coordination problem considering time setting and current setting multiplier. The result shows that the proposed method is fast, accurate and applicable compared to previous work proposed...
This paper presents the possibilities of using classical genetic algorithm as a tool for solving logical images. Results are presented for simple objective function taking into account the quantity of 0's and 1's and the modified objective function basing on the differences in length of each filled block. Brute-force algorithm was used to illustrate the complexity of NP-complete problem.
In this paper a combination of Genetic Algorithm (GA) and a modified version of a very recent and computationally efficient approach to non-dominated sort called Efficient Non-dominated Sorting (ENS) has been introduced to solve the Multi-Objective Job Shop Scheduling Problem (MO-JSSP). Genetic algorithm was used to lead the search towards the Pareto optimality whilst an Efficient Non-dominated Sorting...
This paper explores the use of Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) for solving multi objective optimal power flow problems. The algorithms are tested on the IEEE 30 bus system by simultaneously minimizing cost, power losses and voltage deviation under operational constraints. The Pareto optimal and fuzzy methods are employed to identify the best compromise for conflicting...
In this study, we are interested in the reusable containers management (e.g gases bottles, pallets, maritime containers, etc.). In this context, we address a dynamic reusable containers planning problem in a close-loop supply chain to optimize reusable containers collect, exploitation, storage and redistribution under environmental constraint in the context of reverse logistic. We propose firstly...
Efficiency of any system or organization can be dealt as output divided by input. In case an organization has multiple inputs, the effective input can be treated as a linear combination of inputs and similarly output can be treated as a combination of outputs. This ratio of the linear combination of output divided by input is a fraction. Optimization of this multivariable fraction is a mathematical...
Considering the transportation network affected by the factors like weather and traffic conditions, a multi-objective fourth party logistics routing problem on the time varying networks is proposed. Under the assumption that the transportation cost and time of the Third Party Logistics (3PL) suppliers is dependent on the departure time. The mathematic program model is built. A genetic algorithm is...
Skip-stop operation is a low cost approach to improving transit operating speed. This paper proposes a new methodology to design a skip-stop strategy for urban rail lines aiming to minimize total travel time while at the same time serve the maximum number of passengers in off-peak hours. Different from the conventional “A/B” scheme, the proposed new scheme called the Flexible Skip-Stop Scheme (FSSS)...
Every flexible manufacturing system demands minimization of production completion time, which reduces the constraints and minimize the production quality with increase in final cost and efficiency. Minimization of production completion time basically deals with two objectives i.e. minimizing machine idle time and minimizing earliness-tardiness penalties. The minimization of these two objectives must...
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