Simulation-based decision-making system for optimal mine production plan selection

Price uncertainty is one of the major uncertainties in the life of mine (LOM) planning process which can have a decisive effect on the overall profitability. Today’s mine planning software tools provide block-sequencing optimisation for a given static price assumption that is then used as a basis of managerial decision-making process. This paper proposes a complementary approach to this by introducing a simulation-based decision-making tool that, with the help of simulation, seeks for the optimal mine plan when a managerially estimated price development with minimum and maximum boundaries is used as a data input for the given period. To demonstrate the approach, a realistic gold mine case study is presented with five alternative and technically feasible mine plans calculated in a static optimiser from a commercial mine planning software package. These mine planning scenarios are then subjected to price uncertainty in simulation with and without a price trend assumption to highlight the effect of price on the mine’s expected performance. Based on the results, we derive and demonstrate a simulation-based system that automates the matching of optimal mine plan with the managerial insight of long-term price development.

Trend Analysis of Broiler Chicken Egg Prices in Bengkulu City

Chicken eggs are one of the most common eggs produced by breeders in Bengkulu. The price of purebred chicken eggs is very affordable compared to other types of eggs. The demand for purebred eggs will continue to grow along with the increase in population. This research aims to determine the pattern of price development of broiler chicken eggs in Bengkulu City and the trend of broiler egg prices in Bengkulu City. This research uses Trend Analysis with a simple linear regression method. An estimate made or forecast in the future with statistical analysis methods. It requires a wide variety of data (information) that is quite a lot and visible in a significant enough time to make a measuring instrument so that every component that affects the development to how much change occurs can be seen using this research. The information used was obtained from the Central Bureau of Statistics of Bengkulu City. The result obtained is a positive trend where the line of price development depicted increases continuously. The trend that continues to increase is influenced by several things that occur within a year, including Eid al-Adha, Christmas, and the new year. The linear trend line is Y = 1942,9 + 3,96 X + E where R^2 = 0,5661

The analysis of factors affecting price of selected commodities

Research background: Commodities are attractive investment opportunities and are objects of many researches. Traditional and most stable seem to be precious metals gold and silver. In the global world where anyone can access information in seconds it is crucial to know the background of price development in order to make the right investment decision. Purpose of the article: This paper focuses on international commodity exchanges and analyzes factors affecting prices of selected commodities. It offers a summary of recent studies and continues with an analysis of most relevant factors affecting price of gold and silver. Methods: After collecting data and testing their consistency we construct two hypothesis models. Using linear regression model we test the appropriateness of models which are constructed for each commodity. Subsequently, we test statistical significance of individual explanatory variables, such as dollar exchange rate, VIX, CPI, DJIA, DAX or oil price. Additionally, we take into consideration not traditional factors e.g. Bitcoin. Findings & Value added: Finally an evaluation of results are carried out and the influence of variables are quantified. For instance, negative impact of VIX and dollar exchange rate in observed period of time was confirmed. Given the fact that there can be various other factors influencing price development of gold and silver this paper serves as basis for further analysis in this direction.

Statistical Methods in Building Industry to Determine Prices Indices

Tender price is often affected by the location of the construction, which is usually determined by the investor, and it has an impact on the traffic in the particular location. Individual time of supply and the method of realization play an important role as well. They both are determined by the investor along with the designer of the particular construction. Contractors often complain about the lack of time needed for the preparation of their tender prices. Therefore, it is necessary to look for the possibilities how to reliably speed up this process at the same time taking into account all of the specific features of a structure. This article deals with the application of two statistical methods. The Pareto analysis, which can be used during the design of the tender price, and the extrapolation method, which can be used for the estimation of the price development, based on the regression analysis of the time series. The results of the article particularly serve to contractors in the building industry to better prepare their price offers in tenders. The findings of this document may also be applicable in other countries which have a similar economic profile as Slovakia.

Decision and Coordination of Low-Carbon E-Commerce Supply Chain with Government Carbon Subsidies and Fairness Concerns

More low-carbon products help fight climate change and environmental problems. Governments consider encouraging the manufacturer’s initiative of producing low-carbon products by providing subsidies. However, when the manufacturer sells low-carbon products through the e-commerce platform, fairness concerns arise because of the profit difference. So, this paper builds game models to study decision behavior in the low-carbon e-commerce supply chain when the manufacturer receives government carbon subsidies and has fairness concerns. Our findings show that consumers’ preference for low-carbon products will be conducive to the operation of the supply chain. So it is necessary to popularize low-carbon products. The effect of government subsidies on supply chain decisions is different from fairness concerns. Government subsidies are positive factors in the supply chain operation, which can stimulate the manufacturer to make low-carbon products as expected and choose the high quality-high price development mode. This will help improve the profit of enterprises in the supply chain but cannot effectively stimulate the e-commerce platform to increase its service level. By contrast, the manufacturer’s fairness concerns are negative factors, which make the manufacturer prefer to adopt a low quality-low price development mode to improve their utility. This offsets the positive effect of government subsidies. It turns out that the profit of both node enterprises and the supply chain system has declined. But, fairness concerns are an important way to express the manufacturer’s demand. Finally, the joint allocation contract of cost and profit designed by comprehensively considering the effect of government subsidies and fairness concerns can make the supply chain coordinated. However, even as positive factors, only within a specific range do government subsidies help coordinate the supply chain, but not the more, the better.

Innovations in Management Forecast: Time Development of Stock Prices with Neural Networks

Accurate prediction of stock market values is a challenging task for over decades. Prediction of stock prices is associated with numerous benefits including but not limited to helping investors make wise decisions to accumulate profits. The development of the share price is a dynamic and nonlinear process affected by several factors. What is interesting is the unpredictability of share prices due to the global financial crisis. However, classical methods are no longer sufficient for the application of share price development prediction.However, over-relying on prediction data can lead to losses in the case of software malfunction. This paper aims to innovate the prediction management when predicting the share price development over time by the use of neural networks. For the contribution, the data on the prices of CEZ, a.s. shares obtained from the Prague Stock Exchange database. The stock price data are available for the period 2012-2017. In the case of Statistica software, the multilayer perceptron networks (MLP) and the radial basis function networks (RBF) are generated. In the case of Matlab software, the Support Vector Regression (SVR) and the Back-Propagation Neural Network (BPNN) are generated. The networks with the best characteristics are retained and based on the statistical interpretation of the results, and all are applicable in practice. In all data sets, MLP networks show stable performance better than in the case of SVR and BPNN networks. As for the final assessment, the deviation of 2.26% occurs in the most significant differential of the maximal and the minimal prediction. It is not necessarily significant regarding the price of one stock. However, in the case of purchasing or selling a large number of stocks, the difference may seem significant. Therefore, in practice, the application of two networks is recommended: MLP 1-2-1 and MLP 1-5-1. The first network always represents a pessimistic, minimal prediction. The second one of the recommended networks is an optimistic, maximal prediction. The actual situation should correspond to the interval of the difference between the optimistic and pessimistic prediction. Keywords: Statistica software, Matlab software, stock price development, neural networks, prediction.

ANALISIS VARIASI HARGA BERAS DI PROVINSI RIAU DAN DAERAH PEMASOK

Riau is one of the provinces that is highly dependent on the supplier area, not the producer area, but the rice consumer net. This causes the price of rice to fluctuate, so the observation of rice price development is very important for the Government of Riau Province. Price fluctuations with large variations are a problem whereas price fluctuations with low variations are relatively controllable, so research on the analysis of price variations, important to do. The results show that overall rice price variation in Riau Province and supplier areas in 2006 - 2015 were is relatively stable with an increasing trend but there was a rice price jump in 2008 as a result of the global economic crisis, where food prices are rising while revenues decrease.