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Showing 68 results for Optimization

Afshar A., Marino M.a., Jalali M.r.,
Volume 1, Issue 1 (9-2003)
Abstract

The reliable operation of spillways, in emergency as well as normal conditions, is one of the vital components in dam safety. Free or uncontrolled overflow spillways are the most reliable choice however. They usually impose higher construction cost and /or results in wasting a considerable amount of water or live capacity of the reservoirs. Employing fuse gates might be a way of reconciling dam safety with maximized storage capacity. The operation of the system can be controlled to within a few centimeters, and the entire installation is not lost for floods less than the maximum design flood. The installation offers more or less the same level of safety as ungated spillways, but avoids their inherent storage capacity loss. Optimum design of fuse gates in particular installation calls for a mathematical model. The model developed in this work includes structural, hydraulics and operational constraints while maximizing the expected cost over the useful life of the project. Accounting for the lost benefit (i.e., water lost as a result of gate tilting) has an influenced effect on the optimum design. To test the performance of the model, data from Zarineh Rud dam in Iran has been used and its result is compared with a direct search technique. The model is capable of helping the design engineer to select the best alternative considering different types of constraints.
Afshar M.h.,
Volume 1, Issue 1 (9-2003)
Abstract

In this paper the analysis of the pipe networks is formulated as a nonlinear unconstrained optimization problem and solved by a general purpose optimization tool. The formulation is based on the minimization of the total potential energy of the network with respect to the nodal heads. An analogy with the analysis of the skeletal structures is used to derive tire formulation. The proposed formulation owes its significance for use in pipe network optimization algorithms. The ability and versatility of the method to simulate different pipe networks are numerically tested and the accuracy of the results is compared with direct network algorithms.
Saffar Zadeh M., Bahramian H.r.,
Volume 1, Issue 2 (12-2003)
Abstract

In this paper an attempt is made to develop a model to increase profit-making in air transportation system taking into consideration of the most important problems encountering the system. Utilizing the outcomes of this model, general policies for investing capital to carne out profit-making projects can be recognized.In the presented model the least squares and non-linear optimization methods have been utilized to recognize unknown quantities. In addition, to simplify the developed model and obtain numerical results, the available potential for increasing profit-making in the system has fallen into three major categories. Moreover, profit-making sources have been classified in five distinguished sections.Since recognizing the utilized coefficients in the model claims extensive studies, in most of the cases, the air transport experts and authorities comments have been taken into consideration and an attempt has been made to adapt these coefficients to real values.
Saffar Zadeh M., Karbasi Zadeh B.,
Volume 2, Issue 1 (3-2004)
Abstract

In this paper, optimal bridge management system models have been presented. These optimization models are capable of allocating limited resources to the bridge preservation schemes in order to establish the optimal time of completing the activities. Bridge-based activities are divided into two main groups: repair projects, and maintenance activities and both models are presented in this paper. Particular attention has been made to optimize the management of the two system activities. The dynamic programming approach was utilized to formulate and analyze the two models. The developed models are found to be more accurate and faster than the previous ones.
Bakhtiari Nejad F., Rahai A., Esfandiari A.,
Volume 2, Issue 2 (6-2004)
Abstract

In this paper a structural damage detection algorithm using static test data is presented. Damage is considered as a reduction in the structural stiffness (Axial and/or Flexural) parameters. Change in the static displacement of a structure is characterized as a set of non-linear undetermined simultaneous equations that relates the changes in static response of the structure to the location and severity of damage. An optimality criterion is introduced to solve these equations by minimizing the difference between the load vector of damaged and undamaged structures. The overall formulation leads to a non-linear optimization problem with non-linear equality and linear inequality constraints. A method based on stored strain energy in elements is presented to select the loading location. Measurement locations are selected based on Fisher Information Matrix. Numerical and experimental results of a 2D frame represent good ability of this method in detecting damages in a given structure with presence of noise in measurements.
M.m. Alinia,
Volume 2, Issue 4 (12-2004)
Abstract

One main factor in design of panels subjected to axial loading is their buckling behaviour. The design of stiffeners in a metal or composite plated structure is the key factor for safety and weight reduction. This work presents a parametric study on the optimal types and geometrical properties of stiffeners in plates under in-plane axial loads. The results show that flanged type (such as T or L) longitudinal stiffeners increase the normal critical stresses by at least 28% compared to non-flanged stiffener. It is also shown that the optimum geometric properties of stiffeners correspond to the point when the buckling shape of a plate changes from the overall to local mode. Also it is illustrated that for these optimal instances, there always is a linear relationship between the cross-sectional area ratio and the rigidity ratio of the stiffeners to the plates. Finally, Sample relationships for plates having different number of stiffeners are presented.
S.j. Mousavi, K. Ponnambalam, F. Karray,
Volume 3, Issue 2 (6-2005)
Abstract

A dynamic programming fuzzy rule-based (DPFRB) model for optimal operation of reservoirs system is presented in this paper. A deterministic Dynamic Programming (DP) model is used to develop the optimal set of inflows, storage volumes, and reservoir releases. These optimal values are then used as inputs to a Fuzzy Rule-Based (FRB) model to derive the general operating policies. Subsequently, the operating policies are evaluated in a simulation model while optimizing the parameters of the FRB model. The algorithm then gets back to the FRB model to establish the new set of operating rules using the optimized parameters. This iterative approach improves the value of the performance function of the simulation model and continues until the satisfaction of predetermined stopping criteria. The DPFRB performance is tested and compared to a model which uses the multiple regression based operating rules. Results show that the DPFRB performs well in terms of satisfying the system target performances.
Kaveh A., Shahrouzi M.,
Volume 3, Issue 3 (9-2005)
Abstract

Genetic Algorithm is known as a generalized method of stochastic search and has been successfully applied to various types of optimization problems. By GA s it is expected to improve the solution at the expense of additional computational effort. One of the key points which controls the accuracy and convergence rate of such a process is the selected method of coding/decoding of the original problem variables and the discrete feasibility space to be searched by GAS. In this paper, a direct index coding (DIC) is developed and utilized for the discrete sizing optimization of structures. The GA operators are specialized and adopted for this kind of encoded chromosomes and are compared to those of traditional GA S. The well-known lO-bar truss example from literature is treated here as a comparison benchmark, and the outstanding computational efficiency and stability of the proposed method is illustrated. The application of the proposed encoding method is not limited to truss structures and can also be directly applied to frame sizing problems.
A. Afshar, H. Abbasi, M. R. Jalali,
Volume 4, Issue 1 (3-2006)
Abstract

Water conveyance systems (WCSs) are costly infrastructures in terms of materials, construction, maintenance and energy requirements. Much attention has been given to the application of optimization methods to minimize the costs associated with such infrastructures. Historically, traditional optimization techniques have been used, such as linear and non-linear programming. In this paper, application of ant colony optimization (ACO) algorithm in the design of a water supply pipeline system is presented. Ant colony optimization algorithms, which are based on foraging behavior of ants, is successfully applied to optimize this problem. A computer model is developed that can receive pumping stations at any possible or predefined locations and optimize their specifications. As any direct search method, the mothel is highly sensitive to setup parameters, hence fine tuning of the parameters is recommended.
H. Moharrami, S.a. Alavinasab,
Volume 4, Issue 2 (6-2006)
Abstract

In this paper a general procedure for automated minimum weight design of twodimensional steel frames under seismic loading is proposed. The proposal comprises two parts: a) Formulation of automated design of frames under seismic loading and b) introduction of an optimization engine and the improvement made on it for the solution of optimal design. Seismic loading, that depends on dynamic characteristics of structure, is determined using "Equivalent static loading" scheme. The design automation is sought via formulation of the design problem in the form of a standard optimization problem in which the design requirements is treated as optimization constraints. The Optimality Criteria (OC) method has been modified/improved and used for solution of the optimization problem. The improvement in (OC) algorithm relates to simultaneous identification of active set of constraints and calculation of corresponding Lagrange multipliers. The modification has resulted in rapid convergence of the algorithm, which is promising for highly nonlinear optimal design problems. Two examples have been provided to show the procedure of automated design and optimization of seismic-resistant frames and the performance and capability of the proposed algorithm.
Sh. Afandizadeh Zargari, R. Taromi,
Volume 4, Issue 3 (9-2006)
Abstract

Optimization is an important methodology for activities in planning and design. The transportation designers are able to introduce better projects when they can save time and cost of travel for project by optimization methods. Most of the optimization problems in engineering are more complicated than they can be solved by custom optimization methods. The most common and available methods are heuristic methods. In these methods, the answer will be close to the optimum answer but it isn’t the exact one. For achieving more accuracy, more time has been spent. In fact, the accuracy of response will vary based on the time spent. In this research, using the generic algorithms, one of the most effective heuristic algorithms, a method of optimization for urban streets direction will be introduced. Therefore model of decision making in considered one way – two way streets is developed. The efficiency of model in Qazvin network is shown and the results compared whit the current situation as case study. The objective function of the research is to minimize the total travel time for all users, which is one of the most used in urban networks objectives.
M.h. Afshar, H. Ketabchi, E. Rasa,
Volume 4, Issue 4 (12-2006)
Abstract

In this paper, a new Continuous Ant Colony Optimization (CACO) algorithm is proposed for optimal reservoir operation. The paper presents a new method of determining and setting a complete set of control parameters for any given problem, saving the user from a tedious trial and error based approach to determine them. The paper also proposes an elitist strategy for CACO algorithm where best solution of each iteration is directly copied to the next iteration to improve performance of the method. The performance of the CACO algorithm is demonstrated against some benchmark test functions and compared with some other popular heuristic algorithms. The results indicated good performance of the proposed method for global minimization of continuous test functions. The method was also used to find the optimal operation of the Dez reservoir in southern Iran, a problem in the reservoir operation discipline. A normalized squared deviation of the releases from the required demands is considered as the fitness function and the results are presented and compared with the solution obtained by Non Linear Programming (NLP) and Discrete Ant Colony Optimization (DACO) models. It is observed that the results obtained from CACO algorithm are superior to those obtained from NLP and DACO models.
H.r. Ghafouri, B.s. Darabi,
Volume 5, Issue 2 (6-2007)
Abstract

A new mathematical model for identifying pollution sources in aquifers is presented. The model utilizes Lagrange Constrained Optimization Method (LCOM) and is capable to inversely solve unsteady fluid flow in saturated, heterogeneous, anisotropic confined and/or unconfined aquifers. Throughout the presented model, complete advection-dispersion equation, including the adsorption as well as retardation of contaminant, is considered. The well-known finite element method is used to discretize and solve the governing equations. The model verification is implemented using a hypothetical example. Also, the applicability of the developed code is illustrated by the real field problem of Ramhormoz aquifer in southwestern Iran.
Hon.m. Asce, M.r. Jalali, A. Afshar, M.a. Mariño,
Volume 5, Issue 4 (12-2007)
Abstract

Through a collection of cooperative agents called ants, the near optimal solution to the multi-reservoir operation problem may be effectively achieved employing Ant Colony Optimization Algorithms (ACOAs). The problem is approached by considering a finite operating horizon, classifying the possible releases from the reservoir(s) into pre-determined intervals, and projecting the problem on a graph. By defining an optimality criterion, the combination of desirable releases from the reservoirs or operating policy is determined. To minimize the possibility of premature convergence to a local optimum, a combination of Pheromone Re-Initiation (PRI) and Partial Path Replacement (PPR) mechanisms are presented and their effects have been tested in a benchmark, nonlinear, and multimodal mathematical function. The finalized model is then applied to develop an optimum operating policy for a single reservoir and a benchmark four-reservoir operation problem. Integration of these mechanisms improves the final result, as well as initial and final rate of convergence. In the benchmark Ackley function minimization problem, after 410 iterations, PRI mechanism improved the final solution by 97 percent and the combination of PRI and PPR mechanisms reduced final result to global optimum. As expected in the single-reservoir problem, with a continuous search space, a nonlinear programming (NLP) approach performed better than ACOAs employing a discretized search space on the decision variable (reservoir release). As the complexity of the system increases, the definition of an appropriate heuristic function becomes more and more difficult this may provide wrong initial sight or vision to the ants. By assigning a minimum weight to the exploitation term in a transition rule, the best result is obtained. In a benchmark 4-reservoir problem, a very low standard deviation is achieved for 10 different runs and it is considered as an indication of low diversity of the results. In 2 out of 10 runs, the global optimal solution is obtained, where in the other 8 runs results are as close as 99.8 percent of the global solution. Results and execution time compare well with those of well developed genetic algorithms (GAs).
M.h. Afshar, R. Rajabpour,
Volume 5, Issue 4 (12-2007)
Abstract

This paper presents a relatively new management model for the optimal design and operation of irrigation water pumping systems. The model makes use of the newly introduced particle swarm optimization algorithm. A two step optimization model is developed and solved with the particle swarm optimization method. The model first carries out an exhaustive enumeration search for all feasible sets of pump combinations able to cope with a given demand curve over the required period. The particle swarm optimization algorithm is then called in to search for optimal operation of each set. Having solved the operation problem of all feasible sets, one can calculate the total cost of operation and depreciation of initial investment for all the sets and the optimal set and the corresponding operating policy is determined. The proposed model is applied to the design and operation of a real-world irrigation pumping system and the results are presented and compared with those of a genetic algorithm. The results indicate that the proposed mode in conjunction with the particle swarm optimization algorithm is a versatile management model for the design and operation of real-world irrigation pumping systems.
Abbas Afshar, S. Ali Zahraei, M. A. Marino,
Volume 6, Issue 1 (3-2008)
Abstract

In a large scale cyclic storage system ,as the number of rule parameters and/or number of operating period increase, general purpose gradient-based NLP solvers and/or genetic algorithms may loose their merits in finding optimally feasible solution to the problem. In these cases hybrid GA which decomposes the main problem into two manageable sub-problems with an iterative scheme between GA and LP solvers may be considered as a sound alternative This research develops a hybrid GA-LP algorithm to optimally design and operate a nonlinear, non-convex, and large scale lumped cyclic storage system. For optimal operation of the system a set of operating rules are derived for joint utilization of surface and groundwater storage capacities to meet a predefined demand with minimal construction and operation cost over a 20 seasonal planning period. Performance of the proposed model is compared with a non-cyclic storage system. The management model minimizes the present value of the design and operation cost of the cyclic and non-cyclic systems under specified and governing constraints, employing the developed GA-LP hybrid model. Results show that cyclic storage dominates non-cyclic storage system both in cost and operation flexibility.
M.h. Sebt, E. Parvaresh Karan, M.r. Delavar,
Volume 6, Issue 4 (12-2008)
Abstract

Geographic information systems (GIS) are one of the fastest growing computer-based technologies of past two decades, yet, full potential of this technology in construction has not been realized. Based upon GIS capabilities, construction site layout is one of the areas that GIS could be applied. The layout of temporary facilities (TFs) such as warehouses, fabrication shops, maintenance shops, concrete batch plants, construction equipments, and residence facilities has an important impact on the cost savings and efficiency of construction operations, especially for large projects. The primary objectives of this paper are to describe GIS technology and to present application of GIS technology to construction site layout. The study also delineated the methods of location TFs in construction site. An example application of GIS to location optimization of tower crane and concrete batch plant is provided to demonstrate GIS capabilities as compared with previous models. The spatial and nonspatial data which used in construction site layout process are analyzed and arranged on GIS environment and results showed the GIS can solve site layout problem. Finally, areas of additional research are noted.
Shahriar Afandizadeh, Jalil Kianfar,
Volume 7, Issue 1 (3-2009)
Abstract

This paper presents a hybrid approach to developing a short-term traffic flow prediction model. In this

approach a primary model is synthesized based on Neural Networks and then the model structure is optimized through

Genetic Algorithm. The proposed approach is applied to a rural highway, Ghazvin-Rasht Road in Iran. The obtained

results are acceptable and indicate that the proposed approach can improve model accuracy while reducing model

structure complexity. Minimum achieved prediction r2 is 0.73 and number of connection links at least reduced 20%

as a result of optimization.


M.h. Afshar, A. Afshar, M. A. Mariño, Hon. M. Asce,
Volume 7, Issue 2 (6-2009)
Abstract

This paper presents the application of an iterative penalty method for the design of water distribution pipe networks. The optimal design of pipe networks is first recasted into an unconstrained minimization problem via the use of the penalty method, which is then solved by a global mathematical optimization tool. The difficulty of using a trial and error procedure to select the proper value of the penalty parameter is overcome by an iterative use of the penalty parameter. The proposed method reduces the original problem with a priori unknown penalty parameter to a series of similar optimization problems with known and increasing value of the penalty parameters. An iterative use of the penalty parameter is then implemented and its effect on the final solution is investigated. Two different methods of fitting, namely least squares and cubic splines, are used to continuously approximate the discrete pipe cost function and are tested by numerical examples. The method is applied to some benchmark examples and the results are compared with other global optimization approaches. The proposed method is shown to be comparable to existing global optimization methods.
Sh. Afandizadeh, S.a.h Zahabi, N. Kalantari,
Volume 8, Issue 1 (3-2010)
Abstract

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 models. Most of these programs use optimization

methods that may fail to optimize these models properly. Even when they do converge, there is no assurance that they

have found the global optimum, and it just might be a good approximation of the global minimum. In this research a

heuristic optimization algorithm, simulated annealing (S.A), has been tested for estimating the parameters of a Logit

model for a mode choice problem that had 17 parameters for the city of Isfahan and has been compared with the same

model calculated using GAUSS that uses common and conventional algorithms. Simulated annealing is and algorithm

capable of finding the global optimum and also it’s less likely to fail on difficult functions because it is a very robust

algorithm and by writing the computer program in MATLAB the estimation time has been decreased significantly. In

this paper, this problem has been briefly discussed and a new approach based on the simulated annealing algorithm

to solve that is discussed and also a new path for using this technique for estimating Nested Logit models is opened

for future research by the authors. For showing the advantages of this method over other methods explained above a

case study on the mode choice of Isfahan has been done.



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