dynamic programming

Since the fisheries sector is one of the important economic sectors that plays a significant role in providing income and employment for the coastal people of the country. In order to maintain the stability of aquatic resources and access to numerous economic, biological, social and planning goals in aquatic resources, it seems inevitable (Rezaat Kish and Badam Firoz, 2017). One of the important goals in fisheries management is to maintain the process of fishing and harvesting from Aquatic resources and sustainable fishing levels. In order to measure the achievement of goals in the process of sustainable development, a series of indicators should be used. Fisheries management for sustainable development is a multi-dimensional activity that should be investigated in a wide area that requires information and data, or indicators other than fish stocks and fishing activity (Wang et al., 2014). Increasing awareness by economic experts, formulating policies, principles, rules and regulations and also expression of scientific models and strategies appropriate harvested and productivity of natural resources, suitable field for the growth and development of other sectors (industry, commerce, agriculture and services) provided and will lead to a stable outlook in country.

One of the most important management tools and solutions that can play a constructive role in the sustainability of natural resources is the use of advanced economic models. For this purpose, in this research, after presenting a method to estimate the net value of resource extraction, a dynamic model was designed to optimize the extraction values. The Lagrange coefficient method was also proposed as another solution in this research. This method is essential for optimizing resources that are harvested in the long term.Estimating the present value of net benefits from natural resourcesThe present value of net benefits (NPV) in economics is one of the standard methods for evaluating economic projects. In this method, the cash flow of income and expenses is discounted to the daily rate based on the time of occurrence of income or expenses. In this way, in the cash flow, the time value of spending or earning income is included. Net present value in natural resource economics is used to estimate the present value of resource extraction.The exploitation of natural resources due to rapid population growth and meet the basic human needs of growing and developing. This growth in addition to, production technology developed and harvesting of resources in large scale, emphasis to sustainable economic and environmental activities. According to the vulnerable renewable and non-Renewable resources of countries require that exploit them, for removal existing needs in a manner to be achieved that these resources remain sustainable for coming generation. Achieving this goal requires strong leadership on utilization of existing resources in nature. In this regard, the use of dynamic models for determining optimal amount of harvest and right resource management in the short term and long time periods, necessary to proving to be true this goals and the important role in assist to farmers. For the design of the dynamic optimization model was used Lagrange multiplier method In Chabahar area of Sistan and Baluchestan province in 2021. Excel software was used to solve the model.

Today, the exploitation of natural resources is growing and developing due to the rapid growth of the population and meeting the basic human needs. This growth is in such a way that in addition to the development of the technology of production and harvesting of fishery resources on a large scale, it also emphasizes the economic and environmental sustainability of the activities. In this research presented model to determine optimal amount harvest fishery resources in future periods. This model due to changes in discount rates in various periods of time was to be able to allocate resources in a way that in all periods have maximum profit and net benefits. And causes reduce speed to empty store resource and assist to sustainable of resource. The results showed that the storage of a fishery affected by factors such as the amount of storage, the harvest of the source, the discount rate, rate of return on investment and saving rates is a renewable source. Also the result showed that harvest fish from a fishery over 10 periods with fixed-rate of about 0.05 percent, and started from the second year Total value of net benefits in this case is the equivalent of 15.29 million rials. While that after implementing dynamic planning model amount of fish of resource changed of 0.05 to 0.124. After optimization amount harvest of resource, total net present value by model dynamic planning to estimate 22.75 million rials that indicating increase net present value 7.46 million rials regard to present state. Also the net present value of benefits (NPV) of fish harvested during the 10 consecutive periods reduced to increase discount rate and with discount rate cut has increased. In other words, the relationship between changes in the present value of net benefits and the discount rate indirect or reverse. In addition, by increasing and decreasing the rate of return on investment, increase and decrease the amount of storage. This suggests the existence of a direct relationship between changes rate of return on investment and save the fish is over 10 consecutive periods. And relationship between the rate of return on investment and change of net present value of harvesting fish during 10 consecutive periods.In the end, is recommended the use of dynamic programming models due to its flexibility and ability to calculate time series data in order to allocate renewable natural resources during consecutive periods harvesting of resources. The use of these models to determine the appropriate and schedule program for the harvest of natural resource renewable, cause to protection and stability this resources in long term. In the end, the use of dynamic planning models is recommended due to their flexibility and the ability to calculate time series data in order to allocate renewable natural resources during successive periods of resource extraction. The use of these models, in addition to determining a suitable and scheduled program for the extraction of renewable natural resources, causes the preservation and sustainability of these resources in the long term.

This research presents a new method of coarse-tuning the fuzzy reinforcement learning architecture using agent-environment interactive data. This method solves two main challenges the fuzzy reinforcement learning: the low-speed training process and determining the input membership functions of the fuzzy structure. First, the agent interacts with the environment to gather training data. Then, the transition probability matrix and the expected return matrix are calculated by applying a clustering algorithm due to the continuous space. Each cluster is a state of the environment, and an approximation of the transition probability from one cluster to another is calculated using the gathered data. Finally, the parameters of the fuzzy system are adjusted using the modified value iteration method of dynamic programming for the continuous space. The proposed method is fully described with an example. This method increases the learning speed and adjusts the input membership functions of the fuzzy system.

The purpose of this study was to evaluation the culling rate in two different optimization systems for reproductive and reproductive traits and reproductive and health traits in dairy herds based on data collected from dairy herds in Ardabil province according to market conditions in a production period from 2017 to 2018. One of the most important management decisions affecting livestock profit is timely replacement with young heifers. By analyzing the economic system of the dairy herd system, they were broken down into income and cost components, and each of these components was subdivided into other sub-sections. Then, using mathematical models, a simulation of a bioeconomic model was performed and optimized using MATLAB's Compecon toolbox and dynamic programming. Dairy cows were treated by status variables at three levels (low productivity, medium and high productivity) and reproductive performance at four levels (ideal calving interval, 50,100 and 150 days delay) and health performance at three conditions (no disease, The curable disease, a disease that causes involuntary eradication, was categorized and evaluated in the planning horizon with 10 lactation cycles. The results of the production and reproductive model showed that in the low-production group, the present value increased up to the fourth abdomen and then decreased. And in the intermediate group the present value is increased to the second abdomen and then decreases automatically and in the high productive group the first abdominal value decreases. The results of the production and health models were similar to those of the production and reproductive models in terms of present value changes. Future value is the value of an asset or cash at a specified future date, which is equal to the present value at a present value. It was observed that the trend of future value changes in both systems in different breeding and reproductive status and health and production status decreased with increasing lactation and with increasing cow age. The difference between the future value and the present value under the discount of 20% showed that this difference is further increased by the level of production. Regardless of the present and future value, cows are removed sooner than the optimal deadline, which leads to a decrease in the profitability of the herd. The optimum lifetime determined by dynamic programming was obtained using the Markov simulation for the reproduction and reproduction models of 4.99 years and for reproduction and health of 4.83 years, So that culling of dairy cows older than the optimum age leads to increased profitability of livestock units.

The lack of efficient use of water as a production input has led to wastage of a significant amount of this input, which is financed at a great cost. Most provinces of the country have been facing water crisis for decades. Symptoms of this water crisis have been observed in some plains of Khorasan Province since the early 1970s, and this crisis has intensified in the last decade due to the lack of proper management of water resources. Therefore the present study, using a dynamic approach, studies the management of water resources in the Tabarkabad Dam in Quchan.
In this paper we put forward an easy-to-implement methodology for solving deterministic or stochastic dynamic programming problems within a standard optimization package such as GAMS. We found that the use of orthogonal polynomials was especially helpful in implementing approximation methods for the iterative computation of the infinite-horizon value function, due to their superior convergence properties over standard polynomials. This method is described using the case study of Tabarkabad Dam in Quchan city. For this purpose, data related to the Tabarkabad Dam were collected through the National Dams Information System for the years 2008-2016. Also, data relating to the estimation of the agricultural water demand function in Quchan city were obtained through a questionnaire prepared by the Ministry of Jihad-e-Agriculture.
Based on the results, comparing the actual and simulated values for the dam reservoir (state variable) and water release (control variable), it is determined that the simulations performed with orthogonal polynomial Chebyshev approximation were appropriate. Finally, based on the results, the netpresent value of water allocated to agriculture at Tabarkabad Dam in the studied period is 1471205 Rials and the allocation of water is equal to 24.745 million cubic meters per year.
Considering the results obtained and the proper approximation of simulated values, we can use the proposed method of this study to solve stochastic dynamic programming problems, especially in the field of water resource management. Also, by using the annual allocation of water and taking account of other regional constraints, we can provide a suitable cropping pattern for the sustainable use of agricultural water for the coming years in the fields covered by the Tabarkabad Dam.

In most industrial applications, determining production quantities are one of the most key decision making. In this paper, an integer mathematical programming model for lot-sizing problem with considering set-up time, safety stock, shortage cost, and different production manners, is presented. The objective is to minimize summation of production, set up, holding, and shortage costs. To solve the model, a forward dynamic programming (DP) approach is presented and compared with classical backward DP method. Finally, different numerical illustrations with different dimension are generated. The statistical analysis on computational results showed that the proposed DP approach is more applicable than the classical DP in terms of computational time.