Determining and selecting an appropriate location to construct a hotel is one of the most challenging concerns which hotel industry investors are facing with. In this study we attempt to find a suitable response to this research/application need by a mathematical model using the queueing theory and the fuzzy logic. Therefore hotel, the reception system and travelers accommodations are formulated by appropriate queueing models. Considering the fact that the arrival rate for hotel and the amount of time spent in hotel is uncertain thus a profit function is defined using the fuzzy logic and the fuzzy queueing models. Using the values of this function, candidate locations for constructing a hotel are compared and the one with maximum profit for the investors is selected. Due to using fuzzy parameters in the profit function, the amounts of profit obtained for different locations are in the form of fuzzy numbers, thus we use fuzzy ranking techniques to prioritize the candidate locations for constructing the hotel.

In classic inventory control system, we assume that purchasing cost should be paid at time of delivery. But sometimes in order to encourage retailer to increase his order, postpond payment is provided by supplier as an incentive policy for retailer. In this paper a periodic inventory control model is invetigated in which the period between two consecutive replenishmnet is a random variable. In fact the economic order quantity model under stochastic period lenght and postpond payment is developed. In this paper the concavity of profit function is prooved and situation under which the profit function of retalier is maximized, is determined. The aim of this researchis to determine the the maximum level of inventory such that the total profit is maximized. In continue in order to describe the model numerical examples and sensitivity analysis are introduced.

Operation scheduling of a Virtual Power Plant (VPP) includes several challenges for the system according to the uncertain parameters, and security requirements, which intensify the need for more efficient models for energy scheduling and power trading strategies. Making suitable decisions under uncertainties, related to Renewable Energy Resources (RES), loads, and market prices impose extra considerations for the problem to make a clearer insight for the system operators to participate in local markets. This paper proposes a new risk-based hybrid stochastic model to investigate the effects of wind turbine power fluctuations on profit function, energy scheduling, and market participating strategies. Also, an incentivized Demand Response Program (DRP) is used, to enhance the system’s efficiency. The results of the study indicate that the proposed model based on Information Gap Decision Theory (IGDT) approach makes a clearer environment for the decision-maker to be aware of the effects of risk-taking or a risk-averse strategy on financial profits. The results show that a 30% of robustness and opportunity consideration would change the profit function from -12.5% up to 14.5%, respectively. A modified IEEE 33 bus test system is used to simulate a technical VPP considering the voltage stability and thermal capacity of line requirements.

This research investigated the problem of joint inventory control and pricing for non-instantaneous deteriorating products; while, the quantity dependent trade credit is allowed. It was observed here that the buyer order amount is equal or more than the amount specified by the seller. The Shortage was not permitted in the system. It was aimed in present study to find a procedure for achieving the optimal selling price and replenish cycle and to be able to maximize the system's profit. To do so, first, the system's total profit function was derived. Then, the uniqueness of the optimal replenishment cycle for a given price was proved. Next, the concavity of the total profit function concerning the price was revealed, depending on the trade credit policy. Thereafter, an algorithm was provided to fulfill the optimal solution and eventually a dual-purpose numerical analysis was carried out both to show the model performance and to evaluate the sensitivity of the main parameters.

In this study, yield-water and profit function was used to obtain water demand function in agriculture sector. The results showed that the ratio of actual to potential Evapotranspiration had positive, significant effecton the ratio of actual to potential yield for wheat and barley. Also, square ratio of actual to potential Evapotranspiration had negative, significant relationship. After estimation of product function, water demand function for agriculture sector was obtained by profit function. Price elasticity of water demand for agriculture was -1.10 being less than -1 and showing that price policies can be an important factor in the control of non-optimum use of their valuable inputs.

This paper presents an integrated three layer supply chain policy for multi-channel and multi-echelon consisting manufacturer, distributors and retailers as  supply chain members. The demand of retailers end is considered as linear function of  time and retail price. The average net profit function per unit  time is derived for each  supply chain member which are based on demand of retailer's  end. Since  holding cost of goods/inventory is expensive in developed areas, we have introduced a new concept  to share holding cost among distributors and retailers. We have  optimized lot size, retailing price and replenishment time interval for retailers. We have also optimized initial inventory level and wholesale price for distributors and manufacturer respectively. This  study is performed in two different  categories one is decentralized and other  is centralized scenario. The profit function of each supply  chain members has been derived and shown as a concave function with respect to decision variables. More over propositions and results are made to illustrate the proposed model and we have sensitive  analyzed it with numerical example.

In this paper, greening, pricing, and advertising policies in a supply chain will be examined with government intervention. The supply chain has two members. First, a manufacturer seeking to determine the wholesale price and the greening level and second, a retailer that has to determine the advertising cost and the retail price. The government is trying to encourage the manufacturer to green the production using subsidies. Using the game theory, at first, the demand function and the profit functions of both members are introduced, then in a dynamic game, their Stackelberg equilibrium is calculated. Sensitivity and parameter analysis are made to more illustration of the problem. We found the supply chain profit function behavior and results show that if the sensitivity of demand-price is less than a specific value, the manufacturer will not participate in greening policies.

One of the main factors affecting on the technical and economic performance of farms and livestock is the ability or capacity management. Main goal of farm management is achieving specific performance, profitability and productivity; there for measurement management and performance in livestock farms are necessary. Considering the necessity of increasing production and quality in the dairy industry, to investigate the effect of different inputs and also total factor productivity and management impact on output and profitability, milk production and profit functions, were estimated using Ordinary Least Squares (OLS) method. In this study, data and information were collected by studying documents, observation and interview procedures. Results of production and profit functions estimation showed that productivity and management have positive significant effects on output and profitability. The total factor productivity of them was measured using Tornqvist-Theil indicator; total factor productivity of farms was calculated 0.92 in average. Also, management index for each farm were measured using Multiple Attribute Decision Making (MADM) techniques; the average of management indicator were obtained 0.55. Among the variables included in the production function, two edible inputs; concentrates and alfalfa, and then the labor, respectively have the highest milk production elasticity. It was also showed that the fuel input was used consumedly and in non-economic region of production. Results of profit function estimation showed that fuel price after the price of alfalfa have the greatest negative impact on profitability of dairy farms; on the other hand, concentrates price, wages and cost of each time artificial insemination, have the positive effect on profitability.

The classical inventory models do not consider the real-world competitive situations and management desire to enhance the system and economic parameters such as inflation and time value of money. Studies show that the management wishes an investment in system components in order to improve them and gain a competitive advantage over other businesses. Moreover, the value of system financial resources depends on the time that the use and cash flow of different time is not aggregate. Due to inflation, prices become volatile and change constantly. Therefore, disregard for inflation and time value of money parameters does not lead to optimal ordering policy for inventory systems in reality. For these reasons, it is necessary to consider these components for an inventory system.Previous researchers have conducted various research studies on the performance of inventory systems from various perspectives. Many of these papers did not consider economic parameters and also production environment. During our studies, this study found a gap in the literature that was related to the enhancement of the production capacity in inventory systems in an economic structure. The present paper presents a literature review of time value of money, inflation, and investment in inventory systems and, then, investigates economic production quantity (EPQ) model considering inflation and time value of money in situations, where there is a possibility of investment as a decision variable with the aim of increasing production capacity. The goal of this model is to find economic production quantity and optimal quantity of investment in production capacity so that the total profit function, consisting of system revenues and costs, is optimized. Due to complicated behavior of the proposed model, it is not possible to solve this model analytically. Therefore, a grid search algorithm is proposed for solving the model. The solving algorithm process is investigated by a numerical example. Sensitivity analysis is carried out by changing various parameters. Finally, it is concluded that there is an ascending relationship among the total profit function and the number of algorithm iterations, grid factor, demand rate, selling price, and inflation rate of price; there is also a descending relationship among the total profit function and ordering price, purchase price, rate of return, and inflation rate of sales. At the end, some possible research problems are proposed for the future.

Long-term production planning for open-pit mines is recognised as one of the vital decision-making issues in open-pit mining operations. In addition, the ore grade is one of the most significant sources of uncertainty in a mining operation, as it classified run-of-mine material into ore and waste. In the classical approach, the destination of mining blocks is determined by comparing the estimated grade with a pre-determined cut-off grade. However, the uncertainty of material grade dramatically affects production planning. In this paper, a novel model was developed based on the idea of simulating the grade to incorporate the risk of grade uncertainty. In the proposed model, the economic consequences of the assigned destination are calculated using the profit and loss functions and they are integrated with the production scheduling. The proposed production planning was implemented in an iron ore mine, and the results were discussed for classical, loss, and profit models. Results show that the net present value increases by 3.64% by implementing the profit function. In contrast, the loss function method reduces the net present value by 2.23% compared to the classic model. This happens because the amount of ore class is increased by 7.46% using the profit function method and decreased by 2.49% using the loss function method. Additionally, the coefficient of variation, as an index of uncertainty, was investigated. The results show that the loss function approach attempts to extract more reliable blocks in the early years and postpone the high-uncertain blocks to the later years of the production.