e-learning model is examined of three major dimensions. and each dimension has a range of indicators that is effective in optimization and modeling, in many optimization problems in the modeling, target function or constraints may change over time that as a result optimization of these problems can also be changed. if any of these undetermined events be considered in the optimization process, t...

In this study, a hybridized neuro-genetic optimization methodology realized by embedding numerical simulations trained artificial neural networks (ANN) into a genetic algorithm (GA) is used to optimize the flow rectification efficiency of the diffuser element for a valveless diaphragm micropump application. A higher efficiency ratio of the diffuser element consequently yields a higher flow rate...

Biogeography-Based Optimization (BBO) algorithm has recently been of great interest to researchers for simplicity of implementation, efficiency, and the low number of parameters. The BBO Algorithm in optimization problems is one of the new algorithms which have been developed based on the biogeography concept. This algorithm uses the idea of animal migration to find suitable habitats for solvin...

Optimization of noisy non-linear problems plays a key role in engineering and design problems. These optimization problems can't be solved effectively by using conventional optimization methods. However, metaheuristic algorithms such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) seem very efficient to approach in these problems and became very popular. The efficiency of these ...

This paper introduces the main ideas of the nested partitions (NP) method, analyses its efficiency theoretically and proposes the way to improve the optimization efficiency of the algorithm. Then the paper introduces the simulated annealing (SA) algorithm and incorporates the ideas of SA into two of the arithmetic operators of NP algorithm to form the combined NP/SA algorithm. Moreover, the pap...

Existing ant colony optimization (ACO) for software testing cases generation is a very popular domain in software testing engineering. However, the traditional ACO has flaws, as early search pheromone is relatively scarce, search efficiency is low, search model is too simple, positive feedback mechanism is easy to produce the phenomenon of stagnation and precocity. This paper introduces improve...

Nowadays, the challenge in hydraulic turbine design is the multi-objective design of turbine runner to reach higher efficiency. The hydraulic performance of a turbine is strictly depends on runner blades shape. The present paper focuses on the application of the multi-objective optimization algorithm to the design of a small Francis turbine runner. The optimization exercise focuses on the effic...

A hybrid of evolutionary programming (EP) and a deterministic optimization procedure is applied to a series of nonlinear and quadratic optimization problems. The hybrid scheme is compared with other existing schemes such as EP alone, two-phase (TP) optimization, and EP with a non-stationary Penalty function (NS-EP). The results indicate that the hybrid method can outperform the other methods wh...

In this paper, four simulated annealing based multiobjective algorithms—SMOSA, UMOSA, PSA and WMOSA have been used to solve multiobjective optimization of constrained problems with varying degree of complexity along with a new PDMOSA algorithm. PDMOSA algorithm uses a strategy of Pareto dominant based fitness in the acceptance criteria of simulated annealing and is improved. In all algorithms, ...

Nearly all discussions about the appropriate consumption discount rate for climate-change policy evaluation assume that a single discount rate concept applies. We argue that two distinct concepts and associated rates apply. We distinguish a social-welfare-equivalent discount rate (rSW) appropriate for determining whether a given policy would augment social welfare (according to a postulated soc...