Simulated Annealing Global Optimization Method Research Articles

High Resolution Model of the Vinton Salt-Dome Cap Rock by Joint Inversion of the Full Tensor Gravity Gradient Data with the Simulated Annealing Global Optimization Method

We present a 3D high-resolution modeling methodology based on the interpretation of gravity gradient data and its joint inversion with the simulated annealing (SA) global optimization method. The geometry of the model, used as computational domain in the solution of the forward and inverse problems, is defined with an irregular ensemble of cubic prisms that recreates the interpreted shape of the target, derived from the results of applying different interpretation methods to the gravity gradient data. In our inversion approach, the linear inverse problem resulting from the domain discretization is not solved. Instead, the cost function is explored with the SA algorithm, its low misfit region is identified, and models belonging to it are selected for obtaining the mean model, which represents the most likely model among them, as well as for estimating its uncertainty. The SA inversion algorithm we applied was numerically optimized to reduce the computational burden required by the forward problem, and it was driven by optimal tuning parameters, determined by a parametric analysis. Tests on synthetic data show the efficiency of our methodology to obtain a model that approximates the synthetic target and the usefulness of the estimated uncertainty to complement the interpretation. Finally, by applying our methodology to gravity gradient data acquired over the Vinton dome located in Louisiana, USA, we obtained results that are in agreement with geological information and previous studies.

Sensitivity Analysis of Petrophysical Parameters for Estimating Hydrate Saturation in the Shenhu Area

Acoustic and electrical methods are commonly used to evaluate hydrate saturation based on the P-wave velocity and resistivity, respectively. In this paper, petrophysical parameters, which are directly related to the presence of hydrates, are used to evaluate hydrate saturation. First, five petrophysical parameters sensitive to hydrate saturation are analyzed using the equivalent medium rock physical model (MBGL), logging intersection plots and petrophysical parameter inversion. Then, the simulated annealing global optimization method is used to estimate the hydrate saturation profile in the Shenhu area. The petrophysical parameters Vp, λρ and λμ, which are associated with the rock modulus (both the elastic modulus and shear modulus), are highly sensitive to hydrate saturation, with an estimated saturation range of 0.1-0.44. This range is highly consistent with that based on the original well diameter curves. However, the parameters Vs and μρ, which are only related to the shear modulus of the rock, yield high hydrate saturation estimates of 0.22-0.43 and exhibit some deviations from real data. Due to its sensitivity, Poisson's ratio (σ) is least desirable for hydrate evaluation among the studied parameters. The sensitivity of hydrate saturation depends on the petrophysical model used in studies of the physical properties of hydrate and analyses of hydrate storage.

A Comparative Performance of Least-Square Method and Very Fast Simulated Annealing Global Optimization Method for Interpretation of Self-Potential Anomaly over 2-D Inclined Sheet Type Structure

Abstract: Inversion of self-potential anomaly for 2-D inclined sheets of infinite horizontal extent has been studied. Least-square inversion and very fast simulated annealing global optimization has been used to model the five parameters of self potential anomaly. The method of least square and very fast simulated annealing global optimization method is compared and analyzed. Very fast simulated annealing can model the noisy and field data of self potential anomaly very precisely than linear inversion technique. However, time taken by very fast simulated annealing inversion is larger than linearized inversion. The comparative analysis has been done on synthetic data (noise free and noisy) and two field data from Bavarian woods anomaly, Germany and Surda anomaly, India to show the efficacy of both the methods. The estimated parameters were compared with those from previous studies using various global optimization algorithms, mainly neural network, genetic algorithm and particle swarm optimization on the same field data sets. It can be concluded that the global optimization algorithms considered in this study were able to yield compatible solutions with those from least-square methods. The present global optimization method is in good agreement with the other global optimization methods in terms of results and computation time.

Nonlinear structural joint model updating based on instantaneous characteristics of dynamic responses

This paper proposes a new nonlinear joint model updating method for shear type structures based on the instantaneous characteristics of the decomposed structural dynamic responses. To obtain an accurate representation of a nonlinear system׳s dynamics, the nonlinear joint model is described as the nonlinear spring element with bilinear stiffness. The instantaneous frequencies and amplitudes of the decomposed mono-component are first extracted by the analytical mode decomposition (AMD) method. Then, an objective function based on the residuals of the instantaneous frequencies and amplitudes between the experimental structure and the nonlinear model is created for the nonlinear joint model updating. The optimal values of the nonlinear joint model parameters are obtained by minimizing the objective function using the simulated annealing global optimization method. To validate the effectiveness of the proposed method, a single-story shear type structure subjected to earthquake and harmonic excitations is simulated as a numerical example. Then, a beam structure with multiple local nonlinear elements subjected to earthquake excitation is also simulated. The nonlinear beam structure is updated based on the global and local model using the proposed method. The results show that the proposed local nonlinear model updating method is more effective for structures with multiple local nonlinear elements. Finally, the proposed method is verified by the shake table test of a real high voltage switch structure. The accuracy of the proposed method is quantified both in numerical and experimental applications using the defined error indices. Both the numerical and experimental results have shown that the proposed method can effectively update the nonlinear joint model.

Solving generalized Nash equilibrium problems through stochastic global optimization

Generalized Nash equilibrium problems address extensions of the well-known standard Nash equilibrium concept, making it possible to model and study more general settings. The main difference lies in that they allow both objective functions and constraints of each player to depend on the strategies of other players. The study of such problems has numerous applications in many fields, including engineering, economics, or management science, for instance. In this work we introduce a solution algorithm based on the Fuzzy Adaptive Simulated Annealing global optimization method (Fuzzy ASA, for short), demonstrating that it is possible to transform the original task into a constrained global optimization problem, which can be solved, in principle, by any effective global optimization algorithm, but in this paper our main tool will be the cited paradigm (Fuzzy ASA). We believe that the main merit of the proposed approach is to offer a simpler alternative for solving this important class of problems, in a less restrictive way in the sense of not demanding very strong conditions on the defining functions. Several case studies are presented for the sake of exemplifying the proposal's efficacy.

Nonlinear structural model updating based on instantaneous frequencies and amplitudes of the decomposed dynamic responses

This paper proposes a new nonlinear structural model updating method based on the instantaneous frequencies and amplitudes of the decomposed dynamic responses under forced vibration. The instantaneous frequencies and amplitudes of the decomposed mono-component are first extracted by analytical mode decomposition (AMD) and Hilbert transform. Then, an objective function based on the residuals of instantaneous frequencies and amplitudes between experimental structure and nonlinear model is created for calibration of the nonlinear model. In this paper, the structural nonlinear properties are simulated by using hysteresis material parameters of Bouc–Wen model, and the optimal values of the hysteresis parameters are obtained by minimizing the objective function using the simulated annealing global optimization method. To validate the effectiveness of the proposed method, a three-story nonlinear shear type structure under earthquake and harmonic excitations is simulated as a numerical example. Then, the proposed method is verified by the shake table test of a real high voltage switch structure under forced vibration. The updated nonlinear structural model is further evaluated by the shake table test of the switch structure subjected to a new severe excitation. Both numerical and experimental results have shown that the proposed method can effectively update the nonlinear model and the updated model can be further used to predict the nonlinear responses due to new severe excitations.

Simulated annealing with constrained random walk for structural design of doublet lenses

The authors present an application of a simulated annealing global optimization method for the structural design of doublet lenses in accordance with a prespecified set of Gaussian characteristics and pri- mary aberration targets. This approach eliminates the need for any pre- scription for the starting point in the optimization procedure. An identical approach is implemented for the structural design of both cemented and broken contact doublets. Boundaries for the design variables are taken care of by constraining the random walk of this Monte Carlo algorithm entirely within the feasible configuration space. For the sake of acceler- ating convergence in optimization, few modifications of the basic simu- lated annealing technique are attempted. Some illustrative examples are given. © 1998 Society of Photo-Optical Instrumentation Engineers. (S0091-3286(98)02212-0)

A hybrid technique for TCAD modeling and optimization

This paper focuses on continuous simulated annealing global optimization method to be used in conjunction with statistical response surface modeling and powerful local optimization techniques to improve the design and analysis using TCAD.