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In this paper, the optimal location and characteristics of TADAS dampers in moment resisting steel structures, considering the application of minimum number of TADAS dampers in a building as an objective function and the restriction for destruction of main members is studied. Genetic algorithm in first generation randomly produces different chromosomes representing unique TADAS dampers distributions in structure and the structure corresponding to each chromosome is time history analyzed. Then the damage index for each member and the average weighted damage index for all members are determined. Genetic algorithm evaluates the fitness of each chromosome then selection and crossover as logical operators and mutation as random operator effect the current generation's chromosomes according to their fitness and new chromosomes are generated. Accordingly, successive generations are reproduced in the same way until the convergence condition is fulfilled in final generation and four distributions are suggested as better options. Since these proposed distributions are selected under the one earthquake, therefore, it is better that the four new structures are cost-benefit analyzed in different earthquakes. Finally, the optimal placement for dampers is compared and selected based on a benefit to cost ratio, drift stories and the number of different TADAS types of such structures. The increase in amount of energy dissipated via dampers located in different floors as well as the status of plastic hinges in main members of the structure strengthened with optimum option are the proof of the optimal placement and suitable characteristics for dampers.

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In this paper the conditional location problem is discussed. Conditional location problems have a wide range of applications

in location science. A new meta-heuristic algorithm for solving conditional p-median problems is proposed and results are

compared to those of the previous studies. This algorithm produces much better results than the previous formulations.

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Compared to conventional chlorination methods which apply chlorine at water treatment plant, booster chlorination has almost

solved the problems of high dosages of chlorine residuals near water sources and lack of chlorine residuals in the remote points

of a water distribution system (WDS). However, control of trihalomethane (THM) formation as a potentially carcinogenic

disinfection by-product (DBP) within a WDS has still remained as a water quality problem. This paper presents a two-phase

approach of multi-objective booster disinfection in which both chlorine residuals and THM formation are concurrently optimized

in a WDS. In the first phase, a booster disinfection system is formulated as a multi-objective optimization problem in which the

location of booster stations is determined. The objectives are defined as to maximize the volumetric discharge with appropriate

levels of disinfectant residuals throughout all demand nodes and to minimize the total mass of disinfectant applied with a specified

number of booster stations. The most frequently selected locations for installing booster disinfection stations are selected for the

second phase, in which another two-objective optimization problem is defined. The objectives in the second problem are to

minimize the volumetric discharge avoiding THM maximum levels and to maximize the volumetric discharge with standard levels

of disinfectant residuals. For each point on the resulted trade-off curve between the water quality objectives optimal scheduling of

chlorination injected at each booster station is obtained. Both optimization problems used NSGA-II algorithm as a multi-objective

genetic algorithm, coupled with EPANET as a hydraulic simulation model. The optimization problems are tested for different

numbers of booster chlorination stations in a real case WDS. As a result, this type of multi-objective optimization model can

explicitly give the decision makers the optimal location and scheduling of booster disinfection systems with respect to the tradeoff

between maximum safe drinking water with allowable chlorine residual levels and minimum adverse DBP levels.

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In this paper, a location allocation (LA) problem in construction and demolition (C&D) waste management (WM) is studied. A bi-level model for this problem under a fuzzy random environment is presented where the upper level is the governments who sets up the processing centers, and the lower level are the administrators of different construction projects who control C&D waste and the after treatment materials supply. This model using an improved particle swarm optimization program based on a fuzzy random simulation (IPSO-based FRS) is able to handle practical issues. A case study is presented to illustrate the effectiveness of the proposed approach. Conclusions and future research directions are discussed.

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Since the 1990’s, network reliability has been considered as a new index for evaluating transportation networks under uncertainty. A large number of studies have been revealed in the literature in this field, which are mostly dedicated to developing relevant measures that can be utilized for the evaluation of vulnerable networks under different sources of uncertainty, such as daily traffic flow fluctuations, natural disasters, weather conditions, and so fourth. This paper addresses the resource allocation problem in vulnerable transportation networks, in which multiple performance reliability measures should be met at their desired levels, while the overall cost of upgrading links’ performances should be minimized simultaneously. For this purpose, a new approach has been considered to formulate the two well-known performance measures, connectivity and capacity reliability, along with their application in a bi-objective nonlinear mixed integer goal programming model. In order to take into account the uncertain conditions of supply, links’ capacities have been assumed to be random variables and follow normal distribution functions. A computationally efficient method has been developed that allows calculating the network-wise performance indices simply by means of a set of functions of links’ performance reliabilities. Using this approach, as the performance reliability of links are themselves functions of the random links’ capacities, they can be simply calculated through numerical integration. To achieve desirable levels for both connectivity reliability and capacity reliability (as network-wise performance reliability measures) two distinct objectives have been considered. One of the objectives seeks to maximize each of the measures regardless of what is happening to the other objective function which minimizes the budget. Since optimization models with two conflicting objectives cannot be solved directly, the well-known goal attainment multi-objective decision-making (MODM) approach has been adapted to formulate the model as a single objective model. Then the resultant single objective model has been solved through the generalized gradient method, which is a straightforward solution algorithm coded in existing commercial software such as MATLAB programming software. To show the applicability of the proposed model, numerical results are provided for a simple network. Also, to show the sensitiveness of the model to decision maker’s direction weights, the results of sensitivity analysis are presented..

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We consider the problem of continuous dynamic berth allocation to containerships in a tidal seaport. In some container ports, low water depth in coastal area causes many restrictions on providing vessel's services. Therefore, berth allocation planning for relatively large vessels with high draft is subject to tidal conditions when the vessels are in the access channel as from anchorage area to the quay. Tidal conditions sometimes have a significant effect on possibility of entrance and departure of these ships to or from ports. Shahid Rajaee Port Complex, Iran's largest container seaport and the case study of this research, located at northern coast of Persian Gulf and has low water depth in its area. Historical data of seaside operations in this port is applied to the proposed model. This model also takes into account the variations of water depth in different berths. Simultaneous programming for two or more container terminals and exertion of priority and precedency coefficients based on vessel size and voyage type altogether are other attributes of this model. Here, genetic algorithm in combination with pattern search algorithm was used for solving the problem. Computational experiments have indicated that the proposed heuristic is relatively effective just for small size instances.

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This research examines the behavior of soil-reinforced piles and applied loads based on the analytical method and by using the numerical results of FLAC3D software for comparison with the analytical results. The analysis was based on a method called virtual retaining wall, the following into consideration: an imaginary retaining wall that passes the footing edge the bearing capacity of footing on reinforced soil with piles, which was determined by applying equilibrium between active and passive forces on virtual wall and a pile row that exists beneath the shallow foundation. To calculate the lateral pile resistance here, an analytical equation was then required. The main objective of this paper is to determine the percentage of applied load on pile. Similarly, the effect of adding pile in various positions relative to the present footing (underpinning) was studied in this research. The various parameters of this study included pile length, vertical distance of pile head to shallow footing, pile distance to center of footing and location of the pile. Finally, the findings were compared with the numerical results of FLAC3D and the formerly presented experimental results. Results show that the analytical method, while being close to other methods is more conservative.

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Stabilization of earth slopes with various proposed methods is one of the important concerns of geotechnical engineering. In this practice, despite numerous developments, design conservativeness and high costs of stabilization are the issues yet to be addressed. This paper not only deals with pile location optimization but also studies the effects of the pile length by using line segments slip surface (non-circular). Taking into account the line segments slip surface in stabilization of earth slopes is a new topic which has been addressed in this paper. The line segments slip surface is actual slip surface and for determining the pile location it can lead to the actual length of the pile. The line segments critical slip surface is obtained by using the Alternating Variable Local Gradient (AVLG) optimization method. AVLG is an approach in optimization process and it is based on the Univariate method. The line segments form the initial and critical slip surface. Pile improper installation and inadequate length not only fails to increase the factor of safety, but also reduces it. The analyses are performed using the limit equilibrium (LE) method. Results of these analyses are acceptable and are properly consistent with the results obtained by other researchers.

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Risk allocation is the definition and division of responsibility associated with a possible future loss or gain arising from an identified risk. Quantitative approaches to risk allocation have been developed to overcome the limitations of qualitative approaches, especially the issue of the amount of risk to be borne by each party. This paper presents a cooperative-bargaining game model for quantitative risk allocation that extends the previous existing system dynamics SD-based model. The behavior of contracting parties in the quantitative risk allocation process is modeled as the players’ behavior in a game. The proposed model accounts for both the client costs and the contractor costs to perform the quantitative risk allocation process. To evaluate the performance of the proposed model, it has been employed in a pipeline project. Quantitative risk allocation is performed for the inflation as one of the most important identified risks. It is shown that using the proposed cooperative-bargaining game model, both the client and contractor costs are decreased in comparison to the previous SD-based risk allocation approach.

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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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The construction temporary facilities layout planning (CTFLP) requires an identification of necessary construction temporary facilities (CTFs), an identification of candidate locations and a layout of CTFs at candidate locations. The CTFLP is particularly difficult and complex in large-scale construction projects as it affects the overall operation safety and effectiveness. This study proposes a decision making system to decide on an appropriate CTFLP in large-scale construction projects (e.g. dams and power plants) in a comprehensive way. The system is composed of the input, CTF identification, candidate location identification, layout optimization, evaluation and selection, as well as output stages. The fuzzy logic is employed to address the uncertain factors in real-world situations. In the input stage, the knowledge bases for identifying CTFs and candidate locations are determined. Then, CTFs and candidate locations are identified in the following two stages. In the mathematical optimization stage, a multiobjective mathematical optimization model with fuzzy parameters is established and fuzzy simulation-based Genetic Algorithm is proposed to obtain alternative CTFLPs. The intuitionistic fuzzy TOPSIS method is used to evaluate and select the most satisfactory CTFLP, which is output in the last stage. To demonstrate the effectiveness and efficacy of the proposed method, the CTFLP for the construction of a large-scale hydropower dam project is used as a practical application. The results show that the proposed system can assist the contractor to obtain an appropriate CTFLP in a more efficient and effective manner.