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Showing 4 results for Charged System Search (css)

A. Kaveh, M. Nikaeen,
Volume 11, Issue 3 (9-2013)

In this research, the Charged System Search (CSS) and Enhanced Charged System Search (ECSS) algorithm are used to obtain the optimum design of irregular grillage systems with different spacing and various boundary conditions. The cross-sectional properties of the beams are selected as the design variables and the weight of structure is used as the objective function. The displacement limitations and permissible stress constraints are employed from LRFD-AISC and are considered in the formulation of the design problem. Furthermore, in obtaining the response of the grillage systems, the effect of warping is also taken into account. The comparison of the results shows that warping changes the beam spacing, and different boundary conditions have substantial effects on the optimum design of irregular grillage systems
A. Kaveh, A. Nasrolahi,
Volume 12, Issue 1 (3-2014)

In this paper, a new enhanced version of the Particle Swarm Optimization (PSO) is presented. An important modification is made by adding probabilistic functions into PSO, and it is named Probabilistic Particle Swarm Optimization (PPSO). Since the variation of the velocity of particles in PSO constitutes its search engine, it should provide two phases of optimization process which are: exploration and exploitation. However, this aim is unachievable due to the lack of balanced particles’ velocity formula in the PSO. The main feature presented in the study is the introduction of a probabilistic scheme for updating the velocity of each particle. The Probabilistic Particle Swarm Optimization (PPSO) formulation thus developed allows us to find the best sequence of the exploration and exploitation phases entailed by the optimization search process. The validity of the present approach is demonstrated by solving three classical sizing optimization problems of spatial truss structures.
A. Kaveh, H. Safari,
Volume 12, Issue 3 (9-2014)

The paper presents a hybrid-enhanced algorithm based on CSS for discrete problems whit the focus on traveling salesman problem. The CSS algorithm based on some principles from physics and mechanics, utilize the governing Coulomb law from electrostatics and Newtonian laws of mechanics. However, the CSS is more suitable for continuous problems compared with discrete problems. In this paper, we have tried to resolve this defect of CSS algorithm with the help of local search methods and nearest neighbor for discrete problems whit the focus on traveling salesman problem (TSP). To prove the efficiency of the proposed algorithm, results compared with the results of benchmark problems. Then, the proposed algorithm is used to solve the TSP, using as a method for solving the single row facility layout problem (SRFLP). To prove the efficiency, the results are compared with the results of benchmark problems reported in the recent literatures.
Ali Kaveh, Mstafa Khanzadi, M. Alipour,
Volume 14, Issue 5 (7-2016)

Resource allocation project scheduling problem (RCPSP) has been one of the challenging subjects amongst researchers in the last decades. Most of the researches in this scope have used deterministic variables, however in a real project activities are exposed to risks and uncertainties that cause to delay in project’s duration. There are some researchers that have considered the risks for scheduling, 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 fuzzy resource allocation project scheduling problem (FRCPSP) known as charged system search (CSS) and colliding body optimization (CBO). The results show that both of these algorithms find reasonable solutions, however CBO finds the results in a less computational time having a better quality. A case study is conducted to evaluate the performance and applicability of the proposed algorithms.

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