Urban land use planning which is one of the main components of urban planning typically defined as a multi-objective planning problem in optimal use of urban space and existing facilities. Among numerous land use maps, urban planners are usually interested in choosing the map which is contiguous to the optimal land use map of an interested vision. Reference point multi-objective optimization algorithms provide possibility of introducing the optimal values for different objectives as a reference point and producing optimal solutions near to reference points. In this study, the implementation and efficiency of Reference-Point-Nondominated Sorting Genetic Algorithm II (R-NSGA II) for urban landuse allocation is investigated and a method for chromosomes coding is proposed. Maximizing compatibility of adjacent land use, land suitability, accessibility to roads and main socio-economic centers, and minimizing resistance of land use to change are defined as the main objectives. Then the optimal values of objectives were introduced to the algorithm as reference points. Consequently, planners will be able to select within proposed land use maps according to their priorities. The results of land use allocation modeling for Shiraz city in 2011 indicate that the decision maker is able to choose a better decision with more reliability comparing to situations with a single solution. This achievement indicates proposed model ability for simulation of different scenarios in land use planning.

The use of distributed generation units in distribution networks has attracted the attention of network managers due to their great benefits. In this research, the location and determination of the capacity of distributed generation (DG) units for different purposes has been studied simultaneously. The multi-objective functions in optimization model are reducing the losses of the system line, reducing voltage deviation, increasing voltage stability margin, and decreasing network's short circuit when DG units are considered in the distribution network (DN). To calculate the values of mentioned multi-objective functions, a backward and forward sweep load-flow and a short circuit calculation are used. To solve the problem, a multi-objective optimization algorithm called improved Non-Dominated Sorting genetic algorithm–, II (INSGA-II) is used. This algorithm leads to the creation of various responses that the user can choose, as needed, for each one. A tradeoff method, based on fuzzy set theory, is used to obtain the best optimal solution. The proposed method is examined on the IEEE 33-bus test case while considering different scenarios. In the end, the feasibility and the effectiveness of the proposed algorithm for optimal placement and the sizing of DG in distribution systems have been proved.

Objective The present study aimed to provide a decision model in Internet advertising planning using multiobjective genetic algorithm. The proposed model is a model for distributing advertising resources through the web to optimize the effect of advertising, based on research literature and according to the characteristics of advertising through the web. This model can simultaneously consider the interests of network managers and advertisers. Methodology The present study is in the category of descriptive research in terms of method and nature and is a survey in terms of implementation and also applied in terms of purpose. In this research, since the proposed model is a multi-objective optimization model with high dimensions, the multi-objective genetic optimization algorithm has been used to solve it. Findings In this study, unlike previous studies, by simultaneously considering the conflicting goals of applicants for advertising through the web (reducing advertising costs) and webmasters (increasing profits from the provision of services), about How to better optimize the allocation of advertising resources to the website was discussed and a new decision model was presented that had two conflicting goals. In fact, this multi-objective model not only maximizes website revenue but also reduces the cost to the applicant of advertising; therefore, the mentioned model can be the basis of the work of these two. On the other hand, based on the characteristics of advertising through the web and existing pricing strategies, a hybrid pricing strategy was created based on the variables "cost per thousand views" and "cost per click in this research". Then, a new multi-objective optimization decision model based on this strategy was proposed. In this model, the interests of webmasters and advertisers are considered. Finally, by providing a computational example and numerical results of the simulation, the effectiveness of the model and algorithm is proved. Conclusion The simulation results showed that the optimization model and algorithm are justified and feasible. Also, the set of optimal Pareto answers obtained from solving the model can satisfy the webmasters and applicants for advertising. Using this model, they interact and compromise and try to consider the interests of another person. Considering that by solving the proposed model, unlike other models, the interests of both stakeholders have been considered, the answer set is included in the win-win strategy. Therefore, since the validation of this model is done through simulation, in practice, network administrators can when coding ads on web pages by applying the mathematical relationships provided in the proposed model, the method of calculating the cost of applicants for advertising is logical. And provide a list of possible suggestions to the applicant. In this list, different combinations of simultaneous decision variables at the desired level, by maximizing the income of network managers, minimize the costs of each applicant according to their opinion, which leads to the adoption of more efficient pricing strategies.

Uncertainty analysis in systems evaluation and management has been considered as a logical aspect in engineering estimates in recent decades. Uncertainty generally implies that there is no complete knowledge of the behavior of a system and the specific values of its variables. Currently, the uncertainty problem has been one of the topics of interest in research, decision-making and design in the field of water science and engineering. Furthermore, field observational evaluations have shown that hydrological phenomena are inherently random and can follow probabilistic functions. In the past, univariate probability models have been used to predict hydrological events. But today, it has been shown that hydrological phenomena such as precipitation, runoff, flood, and drought are random and multivariate and should be expressed by the characteristics of intensity, duration and amount. The efficiency of copula functions has been proven as an effective technique in multivariate analysis of hydrological events. This study was aimed to develop the probabilistic-fuzzy framework according to the existing gap in the previous studies. Therefore, long-term rainfall and runoff information were analyzed for generating the decision-making system in Barz Plain, Khuzestan province, Iran. Four parameters of maximum rainfall rate and depth, peak flow and volume of runoff have been analyzed to generate the time series of information. The developed conceptual structure could be addressed in four steps. In the first step, an attempt was made to analyze the relationship between the flood hydrographs in the period from 1973 to 2018 in Barz Plain. Barz plain is located in the eastern north of Khuzestan province, Iran within 31° 18' to 31° 28' latitude and 50° 18' to 51° 26' longitude. Next, a probabilistic model was developed by the MATLAB program. In this model, marginal distribution functions, bivariate frequency analysis and calculation of return periods for rainfall characteristics were evaluated. Moreover, a fuzzy set analysis sub-program was prepared to transfer the effects of rainfall to the runoff. This process was developed within the framework of a multi-objective optimization program that was solved using the NSGAII method. The hydrological information used in this study includes the amount of rainfall and runoff recorded in daily time steps. Analysis of available data revealed about 37 rainfall events that led to the flood. Rainfall characteristics (maximum daily rate (mm/day) and cumulative rainfall depth in one event (mm)) and two characteristics of runoff hydrograph (hydrograph peak flow (m3/s) and runoff volume (million cubic meters (MCM)) were calculated from daily rainfall and runoff information. Therefore, a probabilistic decision model based on copula multivariate functions was developed to predict the variables at different return periods. The relationship between rainfall rate and depth with peak hydrograph flow and runoff volume for flood events over a 37-year period was formulated through fuzzy set theory. The feasible domain of the fuzzy problem was searched using a multi-objective optimization genetic algorithm based on the Non-Dominated Sorting to find the extreme points. The obtained solutions were used as a fuzzy response to calculate the runoff of the Barz plain in Khuzestan province in southwestern Iran. The relationship between rainfall and runoff characteristics showed that the maximum rainfall rate and the peak runoff discharge can be inspired by fuzzy theory and create a logical relationship. The results obtained by Chi-Squared, Anderson Darling and Kolmogorov Smirnov tests for the marginal frequency functions indicated that the Generalized Gamma, Log Normal, Generalized Extreme Values, and Log Pearson functions were the best options for estimating the maximum rate and depth of rainfall and peak flow and volume of runoff, respectively. Correlation coefficient was calculated to evaluate the bivariate model performance for the variables. The results of the maximum likelihood estimator to determine the superior joint function showed that Archimedean Clayton copula fited better than others for rainfall characteristics. Based on the developed concepts, the predicted runoff for Barz plain was estimated between 650 to 850 MCM for a 100-year return period. This return period is recommended for reservoir dam design. Consequently, in the 25-year return period, which is an appropriate time scale for flood diversion systems of water storage reservoirs, flood volume of 140 to 173 MCM with a maximum flow of 850 m3/s has been obtained. This flood can be caused by a rainfall of 78 mm/day or a depth of 137 mm

Most of the water in Iran is used in agricultural sector. In recent years, due to loss of attention to this scares production input and incorrect and excessive use, as well as the droughts, the water shortage issue has turned into a serious crisis. So, the planners should work to make a decision in order to minimizing water consumption and prevent the water  from wasted and misused by providing appropriate cropping pattern and also using advanced technologies of irrigation systems. In this study, the applied model is multi-objective genetic algorithms in MATLAB with nondominated Sorting. For this study, for crop seasons 2011-12 to 2014-15, the data of cultivated areas, yield, price and the costs of productions of irrigated crops including wheat, barley, maize, alfalfa and sugar beet crops were obtained from Office of Agriculture in Zaveh plain, Khorasan-Razavi province. Also, the data of Regional Water Authority of Khorasan Razavi and the water supplied from Senobar Station was used. Some required data were obtained through consultation with experts. Comparing the results of the estimated cultivation areas with the actual statistics of cultivated areas for each crop in each year showed that the optimum cropping area of wheat and barley obtained from the model was lower than the actual cropped area. But, corn crop showed an increase in cultivation area which is highly desirable and increases the irrigation scheduling returns and sustainability of agriculture. Considering the importance of minimization of the deviation of the irrigation schedule presented by the experts and farmers, it is recommended that the irrigation scheduling plan for the farmers should take into account the viewpoints of both the farmers and the experts.

This paper is mainly concerned with some of the theoretical aspects of equitable multi-objective optimization. By using the equitability preference structure, we discuss some properties of the equitably nondominated set, such as nonemptiness, external stability and connectedness. Also, we introduce the concept of proper equitable nondominance, and show that these solutions can be obtained by minimizing a weighted sum of the sort of objective functions where all weights are positive and decreasing. Moreover, we present a hybrid scalarization problem to generate equitably nondominated solutions. This method also provides a necessary condition for the existence of properly equitable nondominated solutions.

One of the efficient, cost-effective, and rapid methods for non-destructive quality evaluation of horticultural and agricultural products is the acoustic analysis response generated by impact. In this research, the possibility of using sound processing resulting from the collision of hazelnuts with a galvanized iron plate for separating large, medium, and small hazelnuts, as well as separating nutty and hollow types, has been investigated. First, hazelnuts were divided into four groups based on size: large, medium, small, and empty. The hazelnuts of each group were weighed to separate the nutty and hollow types from the composition. Based on this approach, a system was designed and developed using a single-impact method to generate sound from hazelnuts upon impact with an iron surface. Artificial intelligence techniques were employed to analyze and classify the product based on features extracted from their acoustic signals. Then, in order to take samples, all hazelnuts were dropped from a height of 35 and 45 cm and hit an iron plate. The sound of the collision was recorded by the microphone. The recorded data is taken from the time domain to the frequency domain by Fast Fourier Transform (FFT) and graded using the features obtained from the gradation. The results of audio tests show that by comparing the direct ratio of weight with amplitude and sound pressure level, a hazelnut that has a pass range of less than 0.121Pa, and a sound pressure level of less than 75.2 dB is hollow or has an immature kernels. The study also revealed that the drop height did not significantly affect the quality classification, and a height of 35 cm, along with a sound pressure level above 75.2 dB, yielded the best results for hazelnuts classification. The results of this research, in combination with the common methods of separating hazelnuts, show that acoustic response analysis as a non-destructive method of grading hazelnuts can reduce their damage in addition to increasing the speed and accuracy of calssification.

A closed-loop supply chain model was proposed to optimize the assignment and position of production and distribution centers, product warehouses, retailers, retailer centers, collection, repair, probabilistic customers, and disposal centers. The goal is to minimize environmental pollution and CO2 emissions by considering CO2 to O2 conversion in vehicle gas converters. Two strategies are explored to determine the best retailer locations based on the predicted movement type (Euclidean Square, Euclidean, Chebyshev, and Rectangular) and expected coverage (time and distance). To compare and select the best strategy, a bi-objective nonlinear programming model was introduced. The model simultaneously examines plans 1 and 2 and chooses the superior plan. Given the strategy selected, a heuristic algorithm is employed to determine the best retailer allocation and locations. Given that the problem is NP-hard in nature, it was solved using a meta-heuristic, the Non-Dominated Sorting genetic algorithm. Finally, to validate the effectiveness, a numerical example is presented and solved using optimization software. The algorithm's findings demonstrate a strong correlation with meta-heuristic algorithms, indicating it as a promising starting point that can be further enhanced by incorporating such methods. For instance, the optimized suggestion algorithm resulted in a reduction of 739 units in carbon dioxide emissions, while the genetic algorithm achieved a reduction of 703 units. Furthermore, the cost computed by the algorithm stands at 7,484,935 units, a figure close to the output of 7,030,846 units generated by the genetic algorithms.