Water Cycle Algorithm (WCA) is a new metaheuristic Algorithm which the fundamental concepts of WCA are derived from nature and are based on the observation of Water Cycle process and how rivers and streams flow to sea in the real world. In this paper, the task of sizing optimization of truss structures including discrete and continues variables carried out using WCA, and the optimization results were compared with other well-known optimizers. The obtained statistical results show that the WCA is able to provide faster convergence rate and also manages to achieve better optimal solutions compared to other efficient optimizers.

In this paper the Water Cycle Algorithm (WCA) is utilized for sizing optimization of space trusses. Finding the optimum design of 3-D structures is a difficult task as the great number of design variables and design constraints are present in optimization of these type of structures. The efficiency of the WCA are demonstrated for truss structures subject to multiple loading conditions and constraints on member stresses and nodal displacement. Numerical results are compared with those reported in the literature where the obtained statistical results demonstrate the efficiency and robustness of WCA where it provided faster convergence rate as well as it found better global optimum solution compared to other metaheuristic Algorithms.

Portfolio selection process is a subject focused by many researchers. Various criteria involved in this process have undergone alterations over time, necessitating the use of appropriate investment decision support tools. An optimization approach used in different sciences is using meta-heuristic Algorithms. In the present study, using Water Cycle Algorithm (WCA), a model was introduced for selecting the optimal portfolio, and then the obtained results were compared with those obtained from Harmony Search (HS) and Imperialist Competitive Algorithm (ICA). For this purpose, using the data of 10-month (April 2016 to January 2017) returns of 50 top companies in the Stock Exchange Market of Iran, the optimal portfolio was estimated using the above-mentioned Algorithms with the aim of maximizing profit and minimizing risk, and then the optimal portfolios obtained from these Algorithms were compared with each other. Results of implementing these Algorithms indicated that despite the high capability of the studied Algorithms to optimize the portfolios, WCA Algorithm had higher capability of portfolio optimization than the other ones.

ObjectiveIndependent auditing plays a fundamental role in improving users' decision-making and market efficiency through validating financial reports. The quality of the work of these auditors depends on several factors, one of the most important of which is their independence. Since the phenomenon of auditor change is related to independence, this phenomenon, which is considered one of the vital issues of every company, should be carefully examined. The phenomenon of auditor change creates a break between auditors and the employer. Predicting the continuation or termination of the relationship between the auditor and the client in the coming years is one of the challenging issues in the field of auditing. In this regard, the purpose of this research is to predict voluntary auditor change (non-continuation of the relationship with the current client) using a meta-heuristic Algorithm (Water Cycle Algorithm, WCA) and to compare the results with the logistic regression method.MethodsThe statistical sample is 185 companies listed on the Tehran Stock Exchange, selected by the systematic elimination method from 2017 to 2023, and their information was collected. Years with mandatory auditor switching are excluded. Then, Excel and Matlab software were used for implementing methods and predicting auditor change. Thirteen financial and non-financial variables that were extracted from the literature were used to predict auditor change in this research. These independent variables include: current ratio, working capital, debt ratio, asset ratio, return on assets, earnings quality, firm size, audit firm size, auditor opinion type, management change, separation between CEO and the chair of the board of directors, accounting conservatism, and firm competition power. Moreover, using the confusion matrix, which includes 4 evaluation criteria: accuracy, precision, sensitivity, and specificity, the results obtained from the Water Cycle Algorithm were compared with the results of logistic regression, a prominent method for forecasting binary variables such as auditor change. Additionally, these Algorithms were run 10 times to ensure the reliability of the results.ResultsIn almost all implementations and based on all 4 performance evaluation criteria, the Water Cycle Algorithm is more suitable than logistic regression for predicting auditor change. In general, the criteria of accuracy, precision, sensitivity, and specificity in predicting the change of auditor using the Water Cycle Algorithm were 89%, 75%, 2%, and 99.9%, respectively. In comparison, the logistic regression criteria were 67%, 74%, 1%, and 99.8%, respectivelyConclusionThe Water Cycle Algorithm can be useful for predicting voluntary auditor changes by users and auditing firms. Audit institutions can use this tool to predict the continuation or non-continuation of their relationship with clients in the coming years and better plan to maximize profitability. Audit clients and companies can also use this tool to forecast future relationships with auditors and plan and schedule more efficiently for selecting the next auditor.

In this research, a metaheuristic Algorithm, called Water Cycle Algorithm (WCA), was developed in MATLAB software, with the purpose of optimal allocation strategies of a multi-reservoirs system (Golestan and Voshmgir dams) located at Gorganrood basin (north of Iran), for a five year period (from 2007-2008 to 2011-2012). At the first step, the performance of the developed Algorithm was successfully assessed through several benchmark functions. Next, it was applied to the monthly allocation of Gorganrood multi-reservoirs system. The objective function was defined as the minimizing of the total deficit for the study period. The results of all applied Algorithms were evaluated by reliability and vulnerability criteria. The results of WCA were compared with other developed evolutionary Algorithms including Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). The WCA, GA and PSO were capable to supply 97. 73, 87. 07 and 94. 3 percent of Golestan dam Water demand, respectively. For the Voshmgir dam, the mentioned models could supply 97. 06, 87. 59 and 94. 47 percent of Water demand, in same order. The temporal reliability (α =0. 9) for WCA, GA and PSO models, was obtained 95, 26. 67 and 58. 33 percent for Golestan dam and 91. 67, 38. 33 and 66. 67 percent for Voshmgir dam, respectively, revealed that the WCA was superior in optimal allocation of multi-reservoirs system.

One of the most practical methods for improving system reliability is making a tradeoff between components reliability and redundancy levels, which is known as reliability-redundancy allocation problem (RRAP). The RRAP aims to maximize the overall system reliability by creating a balance between the component reliabilities and the number of redundant components in each subsystem. In the RRAP, the redundant components are performed in a predetermined order under a redundancy strategy. In this paper, a cold standby redundancy strategy is considered for the redundant components. Besides, a penalty guided Water Cycle Algorithm is adjusted for solving the problem. The proposed Algorithm is implemented on two famous benchmark problems to evaluate the performance of the proposed approach. The obtained numerical results reveal the superiority of the proposed solution method over all previous studies.

Maximum Power Point (MPP) tracker has an important role in the performance of fuel cell (FC) systems improvement. Tow parameters which have effect on the Fuel cell output power are temperature and membrane Water. So contents make the MPP change by with variations in each parameter. In this paper, a new maximum power point tracking (MPPT) method for Proton Exchange Membrane (PEM) fuel cell is proposed. This method is based on Water Cycle Algorithm (WCA). In order to show the performance and the accuracy of the proposed method, a system consisting of one Proton Exchange Membrane (PEM) fuel cell, one boost converter, one WCA based MPP tracker and one load is considered. WCA determines voltage corresponding to the maximum power of FC then one PID controller tunes the duty Cycle of the boost converter. The performance of the proposed method is compared with three other MPPT methods (Perturb and Observe, Voltagebased MPPT and currentbased MPPT). The results show that the proposed MPPT method has a high accuracy and a fast response, they also indicate that the proposed method has the better performance in comparison with the other studied methods.

Due to Water use increasing, attention to optimal Water resources allocation is needed. In recent decades, the use of intelligent evolutionary methods for optimization of Water allocation was focused more by researchers. The aim of this study is to development on Water resources planning model that determined the proper cultivation, optimal exploitation of groundWater and surface Water resources although Water allocation among crops is a way to minimize the adverse effects of dehydration and increase its revenue. In this study, for maximizing profits, estimating crop Water requirements at different periods to optimize the management of cropping patterns and irrigation management in cultivation in Varamin irrigation network using a new evolutionary Algorithm was called the Water Cycle. Then for validation of this method is that a new approach and ensure the integrity of its performance Its results are compared with a genetic Algorithm model and linear programming as our base (R2=0. 9963). The results showed that the area cropping pattern was not optimal and the area under cultivation of crops such as wheat, barley, tomatoes, Bamjan, melon, alfalfa reaches zero and the new paradigm of the largest area under cultivation to industrial goods and then was assigned cucumbers. While our revenues have increased about 11 percent. In addition to amount of Water in different months remain in the network that can be used for many that such as injection into underground aquifers or other crops based on the amount of Water available.