This paper presents an efficient and reliable swarm intelligence-based approach, namely elitist-mutated particle swarm optimization EMPSO technique, to derive reservoir operation policies for multipurpose reservoir systems. Particle swarm optimizers are inherently distributed algorithms, in which the solution for a problem emerges from the interactions between many simple individuals called par...

This paper presents an optimization problem about terminal distribution network path, defining the research problem through its distribution operation process, next to the terminal distribution route optimization. To begin with, dynamic optimization algorithm is built, the first from the target distribution node distribution vehicle, and goods to N customers are delivered, in the most appropria...

Genetic Algorithms (GAs) application in the field of water resources engineering is of recent origin. Genetic Algorithms is one of the tools, which handles nonlinear optimization problems in an efficient manner. Optimal reservoir operation of reservoir for hydropower production involves constrained nonlinear optimization. The constrained problem is converted into unconstrained problem by using ...

Complex tensor contraction expressions arise in accurate electronic structure models in quantum chemistry, such as the Coupled Cluster method. Transformations using algebraic properties of commutativity and associativity can be used to significantly decrease the number of arithmetic operations required for evaluation of these expressions, but the optimization problem is NP-hard. Operation minim...

This paper proposes on-line optimal operation planning and control of cogeneration systems (CGS). CGS is usually connected to various facilities such as refrigerators, reservoirs, and cooling towers. In order to generate optimal operation planning for CGS, startup/shutdown status and/or input/output values of the facilities for each control interval should be determined. The facilities may have...

Optimal system operation, in general, involves the consideration of economy of operation, system security, emissions at fossil-fuel plants, optimal release of water at hydro power plants etc. and aim at improving the efficiency of the power system. In this research work, consideration will be given to two aspects of the optimal system operation, emissions and economy of operation, also known as...

The most important issue in multi-objective optimization problems is to determine the Pareto points along the Pareto frontier. If the optimization problem involves multiple conflicting objectives, the results obtained from the Pareto-optimality will have the trade-off solutions that shaping the Pareto frontier. Each of these solutions lies at the boundary of the Pareto frontier, such that the i...

one of the most important fuel cells (fcs) is proton exchange membrane fuel cells (pemfcs). the outputvoltage of this fc depends on current loads. this paper tries to introduce, implement and control the voltage ofpemfc, during load variations. the output voltage of fuel cell should be constant during load variation. toachieve this goal, a controller should be designed. here, the lead-lag contr...

despite the growing use of evolutionary multi-objective optimization algorithms in different categories of science, these algorithms as a powerful tool in portfolio optimization and specially solving multi-objective portfolio optimization problem is still in its early stages. in this paper, moeas have been used for solving multi-objective portfolio optimization problem in tehran stock market. f...

This paper proposes a new algorithm to find the optimization method of reactive regulation in power system to solve the problem of the var compensation and voltage control in center-substations. Using the daily data collected in power substations, the algorithm is combined with improved ant colony algorithm and Apriori data mining techniques. The mathematic model of var optimization of power sy...