Charged System Search Research Articles

Stratification-Based Wind Power Forecasting in a High-Penetration Wind Power System Using a Hybrid Model

This paper proposes a novel stratification-based wind power forecasting method and develops a hybrid forecasting model at different stratifications using charged system search algorithm. The proposed model applies the concept of segmentation from the theory of optimal stratification to forecast short-term wind power outputs. Additionally, the proposed method elucidates different weighting values of each individual model at different segmentation blocks. Based on the forecasting results, the proposed stratification-based hybrid model outperforms traditional stand-alone models and unstratified hybrid models in terms of forecasting accuracy, which verifies the proposed forecasting model for accurate wind power forecasting.

Application of CBO and CSS for Resource Allocation and Resource Leveling Problem

In construction projects, critical path method (CPM) has been mainly used for project scheduling and planning in the past. The main objective of CPM is to find critical activities and schedule the project in such a way that the project makespan is minimized. Resource allocation project scheduling problem has been one of the most popular issues among construction management researchers in the past decades. Resource leveling problem in the real world is also important and should be considered in the planning of a project. On the other side, since these two objectives have opposite goals in the projects, considering both of these objectives simultaneously has always been a challenging problem. In this paper, we try to solve these problems at the same time. For this purpose, two new metaheuristic algorithms so-called colliding body optimization and charged system search are utilized. Two case examples are solved to show the applicability and performance of the considered algorithms.

Regional bivariate modeling of droughts using L-comoments and copulas

The regional bivariate modeling of drought characteristics using the copulas provides valuable information for water resources management and drought risk assessment. The regional frequency analysis (RFA) can specify the similar sites within a region using L-comoments approach. One of the important steps in the RFA is estimating regional parameters of the copula function. In the present study, an optimization-based method along with the adjusted charged system search are introduced and applied to estimate the regional parameters of the copula models. The capability of the proposed methodology is illustrated by copula functions on drought events. Three commonly used copulas containing Clayton, Frank and Gumbel are employed to derive the joint distribution of drought severity and duration. The result of the new method are compared to the method of moments and after applying several goodness-of-fit tests, the results indicate that the new method provides higher accuracy than the classic one. Furthermore, the results of the upper tail dependence coefficient indicate that the Gumbel copula is the best-fitted copula among the other ones for modeling drought characteristics.

Structural health monitoring using optimising algorithms based on flexibility matrix approach and combination of natural frequencies and mode shapes

In this paper, two methods, including flexibility matrix and combination of natural frequencies and mode shapes, are employed to detect the damage location and its severity by creating objective function, which is defined based on differences between the mathematical model and real structure. The damage of structures is modelled by a reduction in the elasticity modulus of the element. The finite element updating approaches used to make an optimisation problem to minimise objective function. In this study, particle swarm optimisation and charged system search as two novel algorithms are taken to find the best optimisation. A few damaged structures with different scenarios are solved to show superiority of each method over another.

Structural design of vehicle components using gravitational search and charged system search algorithms

Abstract The fuel and cost efficiency in automotive industry is related to the designing of light-weight vehicle components. Main aim of this paper is to show effectiveness of two new optimization algorithms in solving structural design optimization problems. The gravitational search algorithm (GSA) and charged system search algorithm (CSS) are applied to the optimum design of a vehicle component. The results show that both GSA and CSS have a better search capability than the genetic algorithms to find optimum solutions.

Probability calculation of rebars corrosion in reinforced concrete using css algorithms

Reinforcement inside the concrete is protected from corrosion and its damages until several years after the construction. After corrosion initiation, the cross section of reinforcement begins to reduce and often load bearing of the reinforced concrete structure will be reduced significantly. Corrosion of reinforcements in concrete in polluted and contaminated areas can occur in two ways: chloride and carbonation. In this work, meta-heuristic approach of charged system search (CSS) is used to calculate corrosion occurrence probability due to chloride ions penetration. The model efficiency is verified by comparing the available examples in technical literature and results of Monte Carlo analysis. According to the analyses performed, using different probabilistic distributions regardless of probabilistic moments based on real distribution leads to diverse results. In addition, influence of each effective parameter in corrosion occurrence varies by changing other parameters.

DAMAGE DETECTION OF SPACE STRUCTURES USING CHARGED SYSTEM SEARCH ALGORITHM AND RESIDUAL FORCE METHOD

Changes in dynamic properties of structures indicate occurrence of damages in the structures. In this paper, a new two stage algorithm for damage detection of large structure is introduced. A modified Residual Force Method is utilized to locate the damage regions in structures, especially barrel vaults, and then the enhanced Charged System Search (CSS) Algorithm is used to quantify the amount of damage. The proposed method requires modeling the structure in its undamaged state to obtain the dynamic properties such as frequencies and mode shapes of the structure in its damaged state. The validation of the method is investigated by some numerical study on space structures. It is shown that if dynamic properties are not affected by noise, the method can still identify damaged elements, but when measurements are corrupted by noise, the exact determination of damaged region is not possible. To overcome this problem, it is proposed to repeat measuring modal properties several times, and then with utilizing residual force vector and statistical analysis, the damaged region is predicted accurately. In this paper, a modified vector is utilized for enhancing efficiency of the modal Residual Force method and suppressing effect of noise, and then a threshold is defined to distinguish DOFs associated with damaged elements. Then, using the CSS algorithm, severities of damaged elements are assessed.

Hybridization of magnetic charge system search and particle swarm optimization for efficient data clustering using neighborhood search strategy

Clustering is a popular data analysis technique, which is applied for partitioning of datasets. The aim of clustering is to arrange the data items into clusters based on the values of their attributes. Magnetic charge system search (MCSS) algorithm is a new meta-heuristic optimization algorithm inspired by the electromagnetic theory. It has been proved better than other meta-heuristics. This paper presents a new hybrid meta-heuristic algorithm by combining both MCSS and particle swarm optimization (PSO) algorithms, which is called MCSS---PSO, for partitional clustering problem. Moreover, a neighborhood search strategy is also incorporated in this algorithm to generate more promising solutions. The performance of the proposed MCSS---PSO algorithm is tested on several benchmark datasets and its performance is compared with already existing clustering algorithms such as K-means, PSO, genetic algorithm, ant colony optimization, charge system search, chaotic charge system search algorithm, and some PSO variants. From the experimental results, it can be seen that performance of the proposed algorithm is better than the other algorithms being compared and it can be effectively used for partitional clustering problem.

Damage detection based on MCSS and PSO using modal data

In this paper Magnetic Charged System Search (MCSS) and Particle Swarm Optimization (PSO) are applied to the problem of damage detection using frequencies and mode shapes of the structures. The objective is to identify the location and extent of multi-damage in structures. Both natural frequencies and mode shapes are used to form the required objective function. To moderate the effect of noise on measured data, a penalty approach is applied. A variety of numerical examples including two beams and two trusses are considered. A comparison between the PSO and MCSS is conducted to show the efficiency of the MCSS in finding the global optimum. The results show that the present methodology can reliably identify damage scenarios using noisy measurements and incomplete data.

Attraction and diffusion in nature-inspired optimization algorithms

Nature-inspired algorithms usually use some form of attraction and diffusion as a mechanism for exploitation and exploration. In this paper, we investigate the role of attraction and diffusion in algorithms and their ways in controlling the behavior and performance of nature-inspired algorithms. We highlight different ways of the implementations of attraction in algorithms such as the firefly algorithm, charged system search, and the gravitational search algorithm. We also analyze diffusion mechanisms such as random walks for exploration in algorithms. It is clear that attraction can be an effective way for enhancing exploitation, while diffusion is a common way for exploration. Furthermore, we also discuss the role of parameter tuning and parameter control in modern metaheuristic algorithms and then point out some key topics for further research.

Shape optimization of arch dams with frequency constraints by enhanced charged system search algorithm and neural network

The main aim of this paper is to find the optimum shape of arch dams subjected to multiple natural frequency constraints by using an efficient methodology. The optimization is carried out by charged system search algorithm and its enhanced version. Computing the natural frequencies by Finite Element Analysis (FEA) during the optimization process is time consuming. In order to reduce the computational burden, Back Propagation (BP) neural network is trained and utilized to predict the arch dam natural frequencies. It is demonstrated that the optimum design obtained by the Enhanced Charged System Search using the BP network is the best compared with the results of other algorithms. The numerical results show the computational advantageous of the proposed methodology.

Optimum design of laterally-supported castellated beams using CBO algorithm

In this study, two common types of laterally supported castellated beams are considered as design problems: beams with hexagonal openings and beams with circular openings. The main goal of manufacturing these beams is to increase the moment of inertia and section modulus, which results in greater strength and rigidity. These types of open-web beams have found widespread use, primarily in buildings, because of great savings in materials and construction costs. Hence, the minimum cost is taken as the design objective function and the Colliding Bodies Optimization (CBO) method is utilized for obtaining the solution of the design problem. The design methods used in this study are consistent with BS5950 Part 1 and Part 3, and Euro Code 3. A number of design examples are considered to optimize by CBO algorithm. Comparison of the optimal solution of the CBO algorithm with those of the Enhanced Charged System Search (ECSS) method demonstrate the capability of CBO in solving the present type of design problem. It is also observed that optimization results obtained by the CBO algorithm for three design examples have less cost in comparison to the results of the ECSS algorithm. From the results obtained in this paper, it can be concluded that the use of beam with hexagonal opening requires smaller amount of steel material and it is superior to the cellular beam from the cost point of view.

CBO and CSS Algorithms for Resource Allocation and Time-Cost Trade-Off

Resource allocation project scheduling problem (RCPSP) has been one of the challenging subjects among researchers in the last decades. Though several methods have been adopted to solve this problem, however, new metahuristics are available to solve this problem for finding better solution with less computational time. In this paper two new metahuristic algorithms are applied for solving this problem known as charged system search (CSS) and colliding body optimization (CBO). The results show that both of these algorithms find reasonable solutions, however CBO could find the result in a less computational time having a better quality. Two case studies are conducted to evaluate the performance and applicability of the proposed algorithms.

Adaptive Charged System Search Approach to Path Planning for Multiple Mobile Robots

This paper suggests the application of adaptive Charged System Search (CSS) algorithms to the optimal path planning (PP) of multiple mobile robots. An off-line adaptive CSS-based PP approach is proposed and applied to holonomic wheeled platforms in static environments. The adaptive CSS algorithms solve the optimisation problems that aim the minimisation of objective functions (o.f.s) specific to PP and expressed as the weighted sum of four functions that target separate PP objectives. A penalty term is added in certain situations in the first step of the PP approach. The specific features of the adaptive CSS algorithms are the adaptation of the acceleration, velocity, and separation distance parameters to the iteration index, and the substitution of the worst charged particles’ fitness function values and positions with the best performing particle data. The fitness function in the adaptive CSS algorithms corresponds to the o.f., and the search space and agents (charged particles) in the adaptive CSS algorithms correspond to the solution space and to the mobile robots, respectively. A case study and experiments are included validate the new adaptive CSS-based PP approach and to compare it with non- adaptive CSS-, Particle Swarm Optimization- and Gravitational Search Algorithm-based PP approaches.

Damage-based optimization of large-scale steel structures

A damage-based seismic design procedure for steel frame structures is formulated as an optimization problem, in which minimization of the initial construction cost is treated as the objective of the problem. The performance constraint of the design procedure is to achieve repairable damage state for earthquake demands that are less severe than the design ground motions. The Park-Ang damage index is selected as the seismic damage measure for the quantification of structural damage. The charged system search (CSS) algorithm is employed as the optimization algorithm to search the optimum solutions. To improve the time efficiency of the solution algorithm, two simplifying strategies are adopted: first, SDOF idealization of multi-story building structures capable of estimating the actual seismic response in a very short time; second, fitness approximation decreasing the number of fitness function evaluations. The results from a numerical application of the proposed framework for designing a twelve-story 3D steel frame structure demonstrate its efficiency in solving the present optimization problem.

An efficient chaos embedded hybrid approach for hydro-thermal unit commitment problem

This paper establishes a model to deal with the short-term hydrothermal generation scheduling (SHTGS) problem. The problem is composed of three interconnected parts: short-term hydrothermal coordination, thermal unit commitment and economic load dispatch. An efficient hybrid method composed of chaotic backtracking search optimization algorithm and binary charged system search algorithm (CBSA–BCSS) is proposed to solve this problem. In order to analyze the effect of the chaotic map on the performance of the method, three different chaotic maps are adopted to integrate into the proposed method and the corresponding consequences are achieved. Furthermore, efficient heuristic search strategies are adopted to handle with the complicated constraints of the SHTGS system. Finally, a hydrothermal unit commitment system is utilized to verify the feasibility and effectiveness of the proposed method. The results demonstrate the efficiency of the hybrid optimization method and the appropriation of the constraint handling strategies. The comparison of the solutions achieved by different methods shows that the proposed method has higher efficiency in terms of solving SHTGS problem.

An improved magnetic charged system search for optimization of truss structures with continuous and discrete variables

In this study, an improved magnetic charged system search (IMCSS) is presented for optimization of truss structures. The algorithm is based on magnetic charged system search (MCSS) and improved scheme of harmony search algorithm (IHS). In IMCSS some of the most effective parameters in the convergence rate of the HS scheme have been improved to achieve a better convergence, especially in the final iterations and explore better results than previous studies. The IMCSS algorithm is applied for optimal design problem with both continuous and discrete variables. In comparison to the results of the previous studies, the efficiency and robustness of the proposed algorithm in fast convergence and achieving the optimal values for weight of structures, is demonstrated.

An improved CSS for damage detection of truss structures using changes in natural frequencies and mode shapes

Non-destructive structural damage identification can be carried out using the difference between a structure’s characteristics before and after a catastrophic event. An approach is to formulate the problem as an inverse optimization problem, in which the amounts of damage to each element are considered as the optimization variables. The objective is to set these variables such that the characteristics of the model correspond to the experimentally measured characteristics of the actual damaged structure. Since the structures are usually symmetric, this is an optimization problem with several global optimal solutions each representing a probable state of damage, where unlike many other optimization problems, it is not enough to merely find one of these optimal solutions; it is important to capture all such possible states and to compare them. In this paper, structural damage detection of planar and spatial trusses using the changes in structures’ natural frequencies and mode shapes is addressed. An improved Charged System Search algorithm is developed and utilized to tackle the problem of finding as many global optimal solutions as possible in a single run. A 10-bar planar truss and a 72-bar spatial truss are considered as numerical examples. Experimental results show that it is important to incorporate mode shapes in order to determine the actual damage scenario among other possibilities.

Optimal seismic design of Reinforced Concrete shear wall-frame structures

Seismic design of Reinforced Concrete (RC) dual systems is performed as an optimization problem for which the charged system search algorithm is utilized as an optimizer. An efficient structural modeling is also presented for this purpose. Here, first databases are created based on ACI seismic criteria for beams, columns and shear walls. Formulations for optimal seismic design of dual systems (shear wall-frame) are proposed. With some modifications on these formulations, optimal seismic design of RC moment frames can also be performed. This procedure is along with ordinary design constraints and effective seismic design constraints. These constraints consist of beams, columns, shear wall design criteria, and some other seismic provisions. Cost of the structure is considered as the objective function. According to the results of the numerical example, the proposed methodology can be considered as a suitable practical approach for optimal seismic design of reinforced concrete shear wall-frame structures.

Identification on Nonlinear Friction Model and Tracking Control for a Ball-Screw Actuated Stage Using Modified Charge System Search

High precise positioning and high-speed performance are demanded for servo mechanical systems in recent industry. However, the nonlinear friction is a main factor to make the positioning mechanism imprecision. To improve the positioning the positioning precision of stages driven by ball-screws, there are two types of compensations including model and non-model based methods. In this study, the LuGre friction Model is applied to model the nonlinear friction behavior for a ball-screw driven stage. A Modified Charge Search System (MCSS) was proposed to identify the system’s parameter. After the system’s parameters are obtained, a feed-forward control integrated with a disturbance observer is proposed to eliminate the external disturbance and improve its tracking performance.