Competitive effects of redroot pigweed (Amaranthus retroflexus) on the growth indices and yield of corn

Kaveh Sheibany,Mohammad Ali,Baghestani Meybodi,ALireza Atri 한국잡초학회 2009 Weed Biology and Management Vol.9 No.2

Colliding bodies optimization for size and topology optimization of truss structures

Kaveh, A.,Mahdavi, V.R. Techno-Press 2015 Structural Engineering and Mechanics, An Int'l Jou Vol.53 No.5

This paper presents the application of a recently developed meta-heuristic algorithm, called Colliding Bodies Optimization (CBO), for size and topology optimization of steel trusses. This method is based on the one-dimensional collisions between two bodies, where each agent solution is considered as a body. The performance of the proposed algorithm is investigated through four benchmark trusses for minimum weight with static and dynamic constraints. A comparison of the numerical results of the CBO with those of other available algorithms indicates that the proposed technique is capable of locating promising solutions using lesser or identical computational effort, with no need for internal parameter tuning.

A new hybrid meta-heuristic for structural design: ranked particles optimization

Kaveh, A.,Nasrollahi, A. Techno-Press 2014 Structural Engineering and Mechanics, An Int'l Jou Vol.52 No.2

In this paper, a new meta-heuristic algorithm named Ranked Particles Optimization (RPO), is presented. This algorithm is not inspired from natural or physical phenomena. However, it is based on numerous researches in the field of meta-heuristic optimization algorithms. In this algorithm, like other meta-heuristic algorithms, optimization process starts with by producing a population of random solutions, Particles, located in the feasible search space. In the next step, cost functions corresponding to all random particles are evaluated and some of those having minimum cost functions are stored. These particles are ranked and their weighted average is calculated and named Ranked Center. New solutions are produced by moving each particle along its previous motion, the ranked center, and the best particle found thus far. The robustness of this algorithm is verified by solving some mathematical and structural optimization problems. Simplicity of implementation and reaching to desired solution are two main characteristics of this algorithm.

Time-history analysis based optimal design of space trusses: the CMA evolution strategy approach using GRNN and WA

Kaveh, A.,Fahimi-Farzam, M.,Kalateh-Ahani, M. Techno-Press 2012 Structural Engineering and Mechanics, An Int'l Jou Vol.44 No.3

In recent years, the need for optimal design of structures under time-history loading aroused great attention in researchers. The main problem in this field is the extremely high computational demand of time-history analyses, which may convert the solution algorithm to an illogical one. In this paper, a new framework is developed to solve the size optimization problem of steel truss structures subjected to ground motions. In order to solve this problem, the covariance matrix adaptation evolution strategy algorithm is employed for the optimization procedure, while a generalized regression neural network is utilized as a meta-model for fitness approximation. Moreover, the computational cost of time-history analysis is decreased through a wavelet analysis. Capability and efficiency of the proposed framework is investigated via two design examples, comprising of a tower truss and a footbridge truss.

Sizing, geometry and topology optimization of trusses using force method and supervised charged system search

Kaveh, A.,Ahmadi, B. Techno-Press 2014 Structural Engineering and Mechanics, An Int'l Jou Vol.50 No.3

In this article, the force method and Charged System Search (CSS) algorithm are used for the analysis and optimal design of truss structures. The CSS algorithm is employed as the optimization tool and the force method is utilized for analysis. In this paper in addition to member's cross sections, redundant forces, geometry and topology variables are considered as the optimization variables. Minimum complementary energy principle is used directly to analyze the structure. In the presented method, redundant forces are calculated by the CSS in order to minimize the energy function. Combination of the CSS and force method leads to an efficient algorithm in comparison to some of the optimization algorithms.

A new PSRO algorithm for frequency constraint truss shape and size optimization

Kaveh, A.,Zolghadr, A. Techno-Press 2014 Structural Engineering and Mechanics, An Int'l Jou Vol.52 No.3

In this paper a new particle swarm ray optimization algorithm is proposed for truss shape and size optimization with natural frequency constraints. These problems are believed to represent nonlinear and non-convex search spaces with several local optima and therefore are suitable for examining the capabilities of new algorithms. The proposed algorithm can be viewed as a hybridization of Particle Swarm Optimization (PSO) and the recently proposed Ray Optimization (RO) algorithms. In fact the exploration capabilities of the PSO are tried to be promoted using some concepts of the RO. Five numerical examples are examined in order to inspect the viability of the proposed algorithm. The results are compared with those of the PSO and some other existing algorithms. It is shown that the proposed algorithm obtains lighter structures in comparison to other methods most of the time. As will be discussed, the algorithm's performance can be attributed to its appropriate exploration/exploitation balance.

Leech Therapy for Linear Incisional Skin-Wound Healing in Rats

Kaveh Darabi Darestani,Sayid Mahdi Mirghazanfari,Katayoun Gohari Moghaddam,Somayeh Hejazi 사단법인약침학회 2014 Journal of Acupuncture & Meridian Studies Vol.7 No.4

Background: The aim of this study was to investigate the effects of leech therapy (LT), in com- parison with topical phenytoin (PHT), on incisional skin-wound healing in animal models. Methods: This experimental study included 15 male rats (5 animals in 3 groups) with approxi- mately equal body weights (350 ? 10 g). Skin wounds with lengths of 20 mm and depths of 0.5 mm were made on the dorsolateral region of rats 4 cm from the spine. The first group (PHT group) was treated daily with topical PHT (1%) while the second group (LT group) received LT at the beginning of the experiment. The control group received neither the drug nor the therapy. Wound healing was evaluated every day, and the study was continued until the wound had completely healed. Changes in the areas and the appearances of the skin wounds and his- tological differences (at the end of the experiment) were used to investigate the differences in wound healing among the groups. Results: The process of wound healing was significantly faster in the group treated with LT (p < 0.05) than in the group treated with the PHT. Conclusion: The study results showed that LT improved incisional skin-wound healing in rats.

Solving a New Multi-Period Multi-Objective Multi-Product Aggregate Production Planning Problem Using Fuzzy Goal Programming

Kaveh Khalili-Damghani,Ayda Shahrokh 대한산업공학회 2014 Industrial Engineeering & Management Systems Vol.13 No.4

This paper introduces a new multi-product multi-period multi-objective aggregate production planning problem. The proposed problem is modeled using multi-objective mixed-integer mathematical programming. Three objective functions, including minimizing total cost, maximizing customer services level, and maximizing the quality of endproduct, are considered, simultaneously. Several constraints such as quantity of production, available time, work force levels, inventory levels, backordering levels, machine capacity, warehouse space and available budget are also considered. Some parameters of the proposed model are assumed to be qualitative and modeled using fuzzy sets. Then, a fuzzy goal programming approach is proposed to solve the model. The proposed approach is applied on a real-world industrial case study of a color and resin production company called Teiph-Saipa. The approach is coded using LINGO software. The efficacy and applicability of the proposed approach are illustrated in the case study. The results of proposed approach are compared with those of the existing experimental methods used in the company. The relative dominance of the proposed approach is revealed in comparison with the experimental method. Finally, a data dictionary, including the way of gathering data for running the model, is proposed in order to facilitate the reimplementation of the model for future development and case studies.

Constructability optimal design of reinforced concrete retaining walls using a multi-objective genetic algorithm

Kaveh, A.,Kalateh-Ahani, M.,Fahimi-Farzam, M. Techno-Press 2013 Structural Engineering and Mechanics, An Int'l Jou Vol.47 No.2

The term "constructability" in regard to cast-in-place concrete construction refers mainly to the ease of reinforcing steel placement. Bar congestion complicates steel placement, hinders concrete placement and as a result leads to improper consolidation of concrete around bars affecting the integrity of the structure. In this paper, a multi-objective approach, based on the non-dominated sorting genetic algorithm (NSGA-II) is developed for optimal design of reinforced concrete cantilever retaining walls, considering minimization of the economic cost and reinforcing bar congestion as the objective functions. The structural model to be optimized involves 35 design variables, which define the geometry, the type of concrete grades, and the reinforcement used. The seismic response of the retaining walls is investigated using the well-known Mononobe-Okabe analysis method to define the dynamic lateral earth pressure. The results obtained from numerical application of the proposed framework demonstrate its capabilities in solving the present multi-objective optimization problem.

A hybrid CSS and PSO algorithm for optimal design of structures

Kaveh, A.,Talatahari, S. Techno-Press 2012 Structural Engineering and Mechanics, An Int'l Jou Vol.42 No.6

A new hybrid meta-heuristic optimization algorithm is presented for design of structures. The algorithm is based on the concepts of the charged system search (CSS) and the particle swarm optimization (PSO) algorithms. The CSS is inspired by the Coulomb and Gauss's laws of electrostatics in physics, the governing laws of motion from the Newtonian mechanics, and the PSO is based on the swarm intelligence and utilizes the information of the best fitness historically achieved by the particles (local best) and by the best among all the particles (global best). In the new hybrid algorithm, each agent is affected by local and global best positions stored in the charged memory considering the governing laws of electrical physics. Three different types of structures are optimized as the numerical examples with the new algorithm. Comparison of the results of the hybrid algorithm with those of other meta-heuristic algorithms proves the robustness of the new algorithm.