In this paper, an intelligent-gradient based algorithm is proposed to solve time optimal bang-bang control problem. The proposed algorithm is a combination of an intelligent algorithm called improved particle swarm optimization algorithm (IPSO) in the first stage of optimization process together with a gradient-based algorithm called successive quadratic programming method (SQP) in the second s...

Content-based image retrieval (CBIR) has been an active research topic in the last decade. In this paper we proposed an image retrieval method using global and local features. Firstly, for local features extraction, SURF algorithm produces a set of interest points for each image and a set of 64-dimensional descriptors for each interest points and then to use Bag of Visual Words model, a cluster...

efficient and on-time maintenance plays a crucial role inreducing cost and increasing the market share of an industrial unit. preventivemaintenance is a broad term that encompasses a set of activitiesaimed at improving the overall reliability and availability of a systembefore machinery breakdown. the previous studies have addressed thescheduling of preventive maintenance. these studies have co...

  In this paper flexible job-shop scheduling problem (FJSP) is studied in the case of optimizing different contradictory objectives consisting of: (1) minimizing makespan, (2) minimizing total workload, and (3) minimizing workload of the most loaded machine. As the problem belongs to the class of NP-Hard problems, a new hybrid genetic algorithm is proposed to obtain a large set of Pareto-optima...

This paper proposes a novel hybrid algorithm namely APSO-BFO which combines merits of Bacterial Foraging Optimization (BFO) algorithm and Adaptive Particle Swarm Optimization (APSO) algorithm to determine the optimal PID parameters for control of nonlinear systems. To balance between exploration and exploitation, the proposed hybrid algorithm accomplishes global search over the whole search spa...

This paper presents a practical and efficient method to solve large-scale nonlinear equations. The global convergence of this new trust region algorithm is verified. The algorithm is then used to solve the nonlinear equations arising in an Expanded Lagrangian Function (ELF). Numerical results for the implementation of some large-scale problems indicate that the algorithm is efficient for these ...

Augmented Downhill Simplex Method (ADSM) is introduced here, that is a heuristic combination of Downhill Simplex Method (DSM) with Random Search algorithm. In fact, DSM is an interpretable nonlinear local optimization method. However, it is a local exploitation algorithm; so, it can be trapped in a local minimum. In contrast, random search is a global exploration, but less efficient. Here, rand...

logit models are one of the most important discrete choice models and they play an important role in describing decision makers’ choices among alternatives. in this paper the multi-nominal logit models has been used in mode choice modeling of isfahan. despite the availability of different mathematical computer programs there are not so many programs available for estimating discrete choice mode...

Normal 0 false false false EN-US X-NONE AR-SA MicrosoftInternetExplorer4 Measurement of solar radiance demands expensive devices to be used. Alternatively, estimator models are used instead. In this paper, a new method based on the empirical equations is introduced to estimate the monthly average daily global solar radiation on a horizontal surface. The proposed method uses Intelligent Water ...

Global optimization methods play an important role to solve many real-world problems. Flower pollination algorithm (FP) is a new nature-inspired algorithm, based on the characteristics of flowering plants. In this paper, a new hybrid optimization method called hybrid flower pollination algorithm (FPPSO) is proposed. The method combines the standard flower pollination algorithm (FP) with the par...