Business process management systems (BPMS) are vital complex information systems to compete in the global market and to increase economic productivity. Workload balancing of resources in BPMS is one of the challenges have been long studied by researchers. Workload balancing of resources increases the system stability, improves the efficiency of the resources and enhances the quality of their products. Workload balancing of resources in BPMS is considered as an important factor of the performance and the stability in systems. Setting the workload of each source at a certain level increases the efficiency of the resources. The main objectives of this research are the concept of resource workload balance and uniformity of the workload for each source at a specified level. To optimize the balance workload and uniformity of each source, the ​ ​ setting multi-process concurrency was offered and studied. Also, the regulation of multi-process concurrency was mentioned as an optimization problem. In this paper, tuning concurrency of the business process is introduced as a problem in BPMS, which is an application issue to improve at workload balance of resources and uniformity in the workload of each resource. To solve this problem, a delay vector is defined, each element of delay vector makes the synthetic delay at the first of each business process, then a Dynamic optimization algorithm is presented to compute delay vector and the speed of the proposed algorithms is compared with and state-space search algorithm and evolutionary algorithm of PSO. The comparison shows that the speed of the proposed algorithm is 37 hours to 5. 8 years compared to the state-space search algorithm, while the POS algorithm solves the same problem in just 3 minutes. The experimental results on a real dataset show 21. 64 percent improvement in the performance of the proposed algorithm.

In the present study, the results of two numerical finite element models prepared for the Dynamic behavior of a concrete bridge in the rail transport network have been modified using the GP algorithm compared to the field data. In this research, taking into account the logical error for the data obtained from the two numerical models and field survey, in addition to modifying the results of models in the field of frequency, acceleration and displacement, the assumed values in the analyses in the error range should be corrected. The results of the GP algorithm showed the success of the algorithm in reducing errors between numerical and field results; so that the errors are limited in the range of %. The bridge studied in this paper is the Arroyo Bracea Bridge in Spain that is made of concrete beams and slabs. This is a bridge with two 15.25 m spans and a 45-degree angle with I-shaped beams crossing two railways. This bridge is modeled with two finite element methods and then is measured via a field survey to evaluate the results of the both models. Then, the difference between the results of the two numerical models and field survey is reduced by proposing the GP algorithm. This bridge is modeled by SAP2000 using orthotropic plate, isotropic plate and beams model. In both models, 6 degrees of freedom are considered for each point, and the interaction between the train and the bridge is neglected. The values of mass, modulus of elasticity, cross-sectional specifications, and degree of stiffness of the support are determined for each model. Accuracy of Dynamic parameters was obtained from the studied bridge and experimental samplings are conducted from two finite element models. In addition to surveying the Dynamic specifications of the soil around the bridge, in this study, the natural frequency of the bridge is obtained with analysis of modals and values of acceleration and displacement in traffic load conditions by installing the piezoelectric accelerometers at 11 points of the bridge. In this study, the soil characteristics around the bridge were also examined. First, by explaining the basics of the GP algorithm, the algorithm prepared in this article was introduced. The data on cross-sectional values, modulus of elasticity, and mass were selected as effective parameters from the initial data of the models and were randomly recorded along with field data in the error range of 1000. For having data with the same level, the values of parameters were normally distributed. Then, by implementing the algorithm proposed for the initial data of each model, a mathematical equation was presented per field data. These equations, in addition to reducing the error of the results of the model, also modify the initial data by providing correction coefficients. The proposed algorithm reduces the error data by 20.31% for acceleration on the part of the bridge deck.  Given the importance of Dynamic behavior of the bridges in high-speed or heavy-load lines, the high accuracy of the results of the analyses related to this behavior is very important. However, the use of GP algorithm for calibration in analysis of bridge Dynamic behavior is very restricted and there is still a possibility of development and improvement. One of the achievements of this paper is that it can be used in similar issues by providing mathematical equations, modifying initial parameters with correction coefficients, and significant reduction in error values. For further research, it is also suggested to investigate the matching factor in specific vectors in the modal analysis via this method. Determining the optimal values of the proposed algorithm parameters using the other methods and sensitivity analysis of GP algorithm compared to the changes in parameters are among the other proper suggestions for subsequent research.

Logistics Network Design includes network configuration decisions having long-standing influences on other tactical and operational decisions. Recently, regarding environmental issues and customer awareness and global warming closed-loop supply chain network design is taken into consideration. The proposed network for the integrated forward and reverse logistics is developed by formulating a cyclic logistics network problem which decisions for selecting the places of manufactories, distribution centers, dismantlers and disposal centers with the respective operating units were supported with the maximizing the profit. Moreover, the palaces of suppliers and customer zone are predefined in this model. Therefore, this paper presents a mixed integer quadratic Programing for a Dynamic multi-period multi-products closed-loop logistics network. The possibility of opening and closing of each facility at each period and expanding the capacities of facilities is the main feature of the proposed model. After model formulation, the credibility and the performance evaluation are investigated by numerical examples.

Goal Programming (GP) is regarded as one of the most important and powerful techniques for dealing with the complex decision problems that involve multiple and specially conflicting objectives. There are several difficulties with GP. This paper provides an appraisement to the effectiveness of GP in incorporating the decision maker (DM)s preferences. An integrated-systematic classification of different GP models is provided; Also the restrictions of each model are explained, And the General Criterion or Value Function Method is introduced. In order to increase the effectiveness of GP models and to decrease the probable mistakes in defining the DMs preferences, a systematic-interactive-procedure is suggested. This systematic procedure helps DM to select a proper GP model based on his preferences.A numerical example is provided in order to make the proposed procedure easy to understand. Finally, the conclusions andfinal remarks areprovided.

This study, offers a Goal Programming model for optimal allocation of provincial budget resources in order to achieve macroeconomic and social goals of country include unemployment and income inequalities reduction and production and employment and social capital increasing. The designed model determines optimum proportion of provinces in budgetary resources in order to achieve goals. Empirical results based on ten provincial indicators include the unemployment rate, GINI coefficient, literacy rate, internet penetration rate, economic participation rate, the province proportion of domestic production and the province proportion of industrial, mining, services and agricultural value added, show that, there is relative convergence in distribution of proportion in public budget resources, and also achieving goals in the more developed provinces needy higher levels of the budget proportion of the province of the less-developed. Therefore, in order to achieve more balanced development and regional convergence and the elimination of inequalities and spatial heterogeneity and financial recommended the allocation of budgetary resources to less developed provinces must be increase and the budget proportion of the provinces converges.

NP-hard optimization problems are computationally challenging tasks that require significant resources to solve, particularly as problem sizes increase. In this paper, we introduce a novel framework, GiraDP, which converts Dynamic programming problems into graphs and solves these large-scale graphs efficiently. GiraDP addresses NP-hard optimization problems by leveraging advanced graph processing techniques. The framework utilizes Giraph and Hadoop in its architecture to manage extensive datasets and complex computations. It generates input data for Giraph and identifies active vertices that correspond to sub-problems within the larger problem. Our experiments include scenarios with 20, 40, and 60 items, across varying knapsack capacities. The results indicate that while the serial algorithm performs best at low capacities, it fails to handle larger instances due to memory limitations, resulting in heap space errors. In contrast, GiraDP demonstrates superior efficiency and scalability for high capacities and large item sets. The MPI-based approach also shows improved performance over the serial algorithm for larger problems, although it does not match the efficiency of GiraDP. These findings underscore the importance of distributed computing solutions for large-scale optimization problems

Due to the lack of measurements in many regions, wave characteristics are estimated using different methods. Wave climate hindcasting/forecasting is mostly conducted by numerical models or empirical methods. Until now, different empirical methods have been developed for wave hindcasting. However, with the development of high speed processors, several sophisticated numerical models have been developed for wave prediction. These models are mostly phase-averaged spectral wave models developed in three generations. In the last two decades, third generation wave models have been used widely in academic and practical projects. In this regard, Port and Maritime Organization has produced his own model, PMO Dynamic. This model has been developed as a part of first three phases of Monitoring and Modeling of Study of Iranian Coasts project. PMO Dynamic package is a software available for engineering purposes. It has several modules that have been developed for different objectives. Wave model is the module which is used for the generation and transformation of wind waves in coastal areas. In this paper, in order to test the PMO Dynamic model capabilities, it has been applied for the prediction of wave parameters in Bushehr Bay and the results have been compared with MIKE21 SW model and measured data.

The purpose of this study was to investigate reforestation projects based on the principles of sustainable development in the Darabkola watershed in Mazandaran province. Therefore, a goal programming model was used for the consideration of multiple goals. A fuzzy hierarchical process was used to compute the weights of different criteria. The criteria and indicators were determined according to principles of the sustainable development, including those related to economy, environment, production, biodiversity conservation, forest health, and forest cover (e. g., various indicators such as net present value, carbon balance, annual increment of diameter, stem biomass, basal area, diameter variation, mass stability, and ecological productivity). The tree species comprised Acer velutinum, A. cappadocicum, Fraxinus excelsior, Juglans regia, Quercus castaneifolia, Alnus subcordata and Pinus brutia. The results of goal programming model showed that the areas of afforestation with different species were changed compared to the ecological capability assessments. The results showed a zero ha potential for maple, which was initially defined 590. 197 ha based on the assessment of ecological potential. In addition, the results revealed 120. 17 ha increase (547 vs. 667. 21) for F. excelsior, 470. 02 ha increase (535. 96 vs. 1005. 99) for A. cappadocicum and 89. 72 ha reduce (416. 30 vs. 326. 57) for Quercus castaneifolia. The reforested area was unchanged for the other species such as J. regia, A. subcordata and P. brutia. Therefore, a total area of 3091. 01 ha was suggested for the afforestation according to the results of goal programming model.

Background: In intertrochanteric fractures، Dynamic hip screw (DHS) is the most frequently used tool، but several studies did not give good results for this device in reverse-oblique and transverse fractures. Current study aimed to compare fixation results of reverse-oblique intertrochanteric and short-segment subtrochanteric fractures using Dynamic condylar screw (DCS) and DHS in patients referred to Alzahra and Kashani Hospitals in Isfahan, Iran.Methods: In a cross-sectional study، medical files of the patients referred to emergency units of the two hospitals who were diagnosed with intertrochanteric or subtrochanteric fractures and underwent DHS or DCS surgery more than 6 months before were assessed; they were invited for follow-up visit and examination. Written consent forms were taken from all the patients upon their entry; and they were examined in terms of complications including nonunion and failure of device and level of fracture improvement. These cases were evaluated by simple radiography ,too. Results obtained from examination of patients in addition to demographic information were recorded in the data collection form for each patient.Findings: Perfect union was observed in 14 (of 25) patients in DHS group and 21 (of 25) patients in DCS group (56% vs. 84%) six months after the surgery. Bone union was significantly better in DCS group (P=0.031). In addition, six months after the surgery, the devices used in 14 people in DHS group and 24 people in DCS group were fixed and the difference between the two groups was significant (P=0.001). 14 and 24 patients had total recovery in DHS and DCS groups، respectively (20% vs. 44%) with a significant difference (P=0.020).Conclusion: Considering obtained results, it can be concluded that using DCS is recommended over DHS due to severity of pain, bone union and fixation of the device.