NPV risk simulation of an open pit gold mine project under the O'Hara cost model by using Gas

This paper analyzes an open pit gold mine project based on the O'Hara cost model. Hypothetical data is proposed based on different authors that have studied open pit gold projects, and variations are proposed according to the probability distributions associated to key variables affecting the NPV, like production level, ore grade, price of ore, and others, so as to see what if, in a gold open pit mine project of 3000 metric tons per day of ore. Two case scenarios were analyzed to simulate the NPV, one where there is low certainty data available, and the other where the information available is of high certainty. Results based on genetic algorithm metaheuristic simulations, which combine basically Montecarlo simulations provided by the Palisade Risk software, the O'Hara cost model, net smelter return and financial analysis tools offered by Excel are reported, in order to determine to which variables of the project is more sensitive the NPV.

A software cost model with maintenance and risk costs for safety-critical systems

According to the consequences of software failures, software faults remaining in safety-critical systems can be classified into two sets： common faults and fatal faults. Common faults cause slight loss when they are activated. A fatal fault can lead to significant loss, and even damage the safety-crltical system entirely when it is activated. A software reliability growth model for safety-critical systems is developed based on G - 0 model. And a software cost model is proposed too. The cost model considers maintenance and risk costs due to software failures. The optimal release policies are discussed to minimize the total software cost. A numerical exampie is provided to illustrate how to use the results we obtained.

Linear Programs in Cost Accounting： A Linear Cost Model

This paper aims to find unit cost of a product for firms. It establishes a linear cost model to find unit cost. Linear goal programs assume a direct relationship between independent variable and dependent variable. Dependent variable of linear model is unit cost. Independent variables are cost accounting variables. They are supply cost, labor cost, and administration cost. This study assumes a direct relationship between supply-labor-administration costs and unit cost. Therefore, it establishes a linear cost model. The major research question of this study is to apply linear goal programming to cost accounting. The goal of this linear program is to find unit cost of product. This study uses quantitative method and human capital method. The main research result is linear costing model itself.

A Heuristics-Based Cost Model for Scientic Workow Scheduling in Clou

Scientic Workow Applications(SWFAs)can deliver collaborative tools useful to researchers in executing large and complex scientic processes.Particularly,Scientic Workow Scheduling(SWFS)accelerates the computational procedures between the available computational resources and the dependent workow jobs based on the researchers’requirements.However,cost optimization is one of the SWFS challenges in handling massive and complicated tasks and requires determining an approximate(near-optimal)solution within polynomial computational time.Motivated by this,current work proposes a novel SWFS cost optimization model effective in solving this challenge.The proposed model contains three main stages:(i)scientic workow application,(ii)targeted computational environment,and(iii)cost optimization criteria.The model has been used to optimize completion time(makespan)and overall computational cost of SWFS in cloud computing for all considered scenarios in this research context.This will ultimately reduce the cost for service consumers.At the same time,reducing the cost has a positive impact on the protability of service providers towards utilizing all computational resources to achieve a competitive advantage over other cloud service providers.To evaluate the effectiveness of this proposed model,an empirical comparison was conducted by employing three core types of heuristic approaches,including Single-based(i.e.,Genetic Algorithm(GA),Particle Swarm Optimization(PSO),and Invasive Weed Optimization(IWO)),Hybrid-based(i.e.,Hybrid-based Heuristics Algorithms(HIWO)),and Hyper-based(i.e.,Dynamic Hyper-Heuristic Algorithm(DHHA)).Additionally,a simulation-based implementation was used for SIPHT SWFA by considering three different sizes of datasets.The proposed model provides an efcient platform to optimally schedule workow tasks by handing data-intensiveness and computational-intensiveness of SWFAs.The results reveal that the proposed cost optimization model attained an optimal Job completion time(makespan)and total computational cost for small and large sizes of the considered dataset.In contrast,hybrid and hyper-based approaches consistently achieved better results for the medium-sized dataset.

Reactive Power and FACTS Cost Models’ Impact on Nodal Pricing in Hybrid Electricity Markets

In a competitive environment reactive power management is an essential service provided by independent system operator taking into account the voltage security and transmission losses. The system operator adopts a transparent and non-dis-criminatory procedure to procure the reactive power supply for optimal deployment in the system. Since generators’ are the main source of reactive power generation and the cost of the reactive power should be considered for their noticeable impact on both real and reactive power marginal prices. In this paper, a method based on marginal cost theory is presented for locational marginal prices calculation for real and reactive power considering different reactive power cost models of generators’ reactive support. With the presence of FACTS controllers in the system for more flexible operation, their impact on nodal prices can not be ignored for wheeling cost determination and has also to be considered taking their cost function into account. The results have been obtained for hybrid electricity market model and results have also been computed for pool model for comparison. Mixed Integer Non-linear programming (MINLP) approach has been formulated for solving the complex problem with MATLAB and GAMS interfacing. The proposed approach has been tested on IEEE 24-bus Reliability Test System (RTS).

Intelligent Cost Modeling Based on Soft Computing for Avionics Systems

In parametric cost estimating, objections to using statistical Cost Estimating Relationships （CERs） and parametric models include problems of low statistical significance due to limited data points, biases in the underlying data, and lack of robustness. Soft Computing （SC） technologies are used for building intelligent cost models. The SC models are systemically evaluated based on their training and prediction of the historical cost data of airborne avionics systems. Results indicating the strengths and weakness of each model are presented. In general, the intelligent cost models have higher prediction precision, better data adaptability, and stronger self-learning capability than the regression CERs.

A Building Information Modeling-Life Cycle Cost Analysis Integrated Model to Enhance Decisions Related to the Selection of Construction Methods at the Conceptual Design Stage of Buildings

Life Cycle Cost Analysis (LCCA) provides a systematic approach to assess the total cost associated with owning, operating, and maintaining assets throughout their entire life. BIM empowers architects and designers to perform real-time evaluations to explore various design options. However, when integrated with LCCA, BIM provides a comprehensive economic perspective that helps stakeholders understand the long-term financial implications of design decisions. This study presents a methodology for developing a model that seamlessly integrates BIM and LCCA during the conceptual design stage of buildings. This integration allows for a comprehensive evaluation and analysis of the design process, ensuring that the development aligns with the principles of low carbon emissions by employing modular construction, 3D concrete printing methods, and different building design alternatives. The model considers the initial construction costs in addition to all the long-term operational, maintenance, and salvage values. It combines various tools and data through different modules, including energy analysis, Life Cycle Assessment (LCA), and Life Cycle Cost Analysis (LCCA) to execute a comprehensive assessment of the financial implications of a specific design option throughout the lifecycle of building projects. The development of the said model and its implementation involves the creation of a new plug-in for the BIM tool (i.e., Autodesk Revit) to enhance its functionalities and capabilities in forecasting the life-cycle costs of buildings in addition to generating associated cash flows, creating scenarios, and sensitivity analyses in an automatic manner. This model empowers designers to evaluate and justify their initial investments while designing and selecting potential construction methods for buildings, and enabling stakeholders to make informed decisions by assessing different design alternatives based on long-term financial considerations during the early stages of design.

基于COST-DEA指数法对某三甲医院临床病区成本效率分析

目的测量某三甲医院各临床病区的成本效率、技术效率和配置效率,为实现医院高质量发展和精细化管理提供数据参考。方法利用数据包络法中的CCR、BCC和COST-DEA模型,测量该三甲医院各临床病区的相关效率值。结果2019年该三甲医院各临床病区的成本效率均值为0.675,配置效率均值为0.782,技术效率均值为0.853,纯技术效率均值为0.902,规模效率均值为0.944。51个临床病区中,7个处于规模报酬递增状态,占比13.73%;23个处于规模报酬不变状态,占比45.10%;21个处于规模报酬递减状态,占比41.17%。结论该三甲医院各临床病区成本效率主要受到配置效率的影响,需要合理配置医疗资源;部分临床病区需要提高内部精细化管理水平实现产出增加。

Charging Ahead with E-Buses: Benefits, Costs, and Transition Roadmap

This paper reaches a recommendation for the 10-year e-bus transition roadmap for New York City. The lifecycle model of emission reduction demonstrates the ecological and financial impacts of a complete transition from the current diesel bus fleet to an all-electric bus fleet in New York City by 2033. This study focuses on the NOx pollution, which is the highest among all major cities by Environmental Protection Agency (EPA) and greenhouse gases (GHG) with annual emissions of over five million tons. Our model predicts that switching to an all-electric bus fleet will cut GHG emissions by over 390,000 tons and NOx emissions by over 1300 tons annually, in addition to other pollutants such as VOCs and PM 2.5. yielding an annual economic benefit of over 75.94 million USD. This aligns with the city mayor office’s initiative of achieving total carbon neutrality. We further model an optimized transition roadmap that balances ecological and long-term benefits against the costs of the transition, emphasizing feasibility and alignment with the natural replacement cycle of existing buses, ensuring a steady budgeting pattern to minimize interruptions and resistance. Finally, we advocate for collaboration between government agencies, public transportation authorities, and private sectors, including electric buses and charging facility manufacturers, which is essential for fostering innovation and reducing the costs associated with the transition to e-buses.

A Review of Energy-Related Cost Issues and Prediction Models in Cloud Computing Environments

With the expansion of cloud computing,optimizing the energy efficiency and cost of the cloud paradigm is considered significantly important,since it directly affects providers’revenue and customers’payment.Thus,providing prediction information of the cloud services can be very beneficial for the service providers,as they need to carefully predict their business growths and efficiently manage their resources.To optimize the use of cloud services,predictive mechanisms can be applied to improve resource utilization and reduce energy-related costs.However,such mechanisms need to be provided with energy awareness not only at the level of the Physical Machine(PM)but also at the level of the Virtual Machine(VM)in order to make improved cost decisions.Therefore,this paper presents a comprehensive literature review on the subject of energy-related cost issues and prediction models in cloud computing environments,along with an overall discussion of the closely related works.The outcomes of this research can be used and incorporated by predictive resource management techniques to make improved cost decisions assisted with energy awareness and leverage cloud resources efficiently.

Green Investment Cost Optimization Model in the Supply Chain

The objective of this study is to develop a model that determines the optimal points for investment in green management by defining a mathematical relationship between carbon trading profits and investments in green management using a company’s supply chain information. To formulate this model, we first define and analyze a green supply chain in a multi-dimensional and quantitative manner. The green investment alternatives considering in our model are as follows: 1) purchasing eco-friendly raw materials that cost more than conventional raw materials but whose use in production results in lower CO2 emissions;2) replacing current facilities with new eco-friendly facilities that have the capability to reduce CO2 emissions;and 3) changing modes of transport from less eco-friendly to more eco-friendly modes. We propose a green investment cost optimization (GICO) model that enables us to determine the optimal investment points. The proposed GICO model can support decision-making processes in green supply chain management environments.

Minimizing Energy Cost of Air Conditioner in a Residential House under Demand Side Response Model

This research is aimed to develop a consumer demanding side response model to assist electricity consumers to mitigate peak demands during the peak season. The main contribution of this research is showing that consumers can mitigate peak demands by optimizing energy costs of an air conditioner(AC) when a spike happens. It may only occur in a one and a half hours spike during the peak season. This model also investigates how AC applies the pre-cooling method when there is a substantial risk of a price spike. The results indicate that the potential benefit of the model is achieving energy savings for consumers and aggregators,also reducing electricity bills for the consumers. The model is tested with selected characteristics of the room,and based on the standard room in a residential house in Makassar, a city of Indonesia.

Optimal pricing decision model based on activity-based costing

In order to find out the applicability of the optimal pricing decision model based on conventional cost behavior model after activity based costing has given strong shock to the conventional cost behavior model and its assumptions, detailed analyses have been made using the activity based cost behavior and cost volume profit analysis model, and it is concluded from these analyses that the theory behind the construction of optimal pricing decision model is still tenable under activity based costing, but the conventional optimal pricing decision model must be modified as appropriate to the activity based costing based cost behavior model and cost volume profit analysis model, and an optimal pricing decision model is really a product pricing decision model constructed by following the economic principle of maximizing profit.

Modelling spatial variation in the treatment costs of nonpoint source pollution in mountainous regions of southwest China

Non-point source(NPS) pollution is considered to be one of the main threats of the aquatic environment. Mountainous regions are particularly important water sources for urban areas. The various driving factors of NPS pollution such as terrain, precipitation, and vegetation type in mountainous regions show clear spatial heterogeneity. Consequently, the management systems required for NPS pollution in mountainous regions are complex. In this study, we developed a framework to estimate and map the treatment costs for NPS pollution in mountainous regions and applied this method in Baoxing County, a typical mountainous county in Sichuan Province of southwest China. The export levels of total nitrogen(TN) and total phosphorus(TP) in Baoxing County were estimated using the water purification model in InVEST(Itegrated Valuation of Ecosystem Services and Tradeoffs) tool. NPS pollutant treatment costs were calculated based on the level of pollutants exports, water yield, water quality targets, and treatment costs of NPS pollutants per unit mass. The results show that at the watershed level the amounts of TN and TP exported in Baoxing County were below threshold limits. However, at the sub-watershed level, TN and TP excesses of 291.64 and 2.96 tons per year were found, respectively, with mean TN and TP treatment costs of 6.58 US$/hm^2 and 0.35 US$/hm^2. Appraising pollution treatment cost intuitively reflects the overall expenditure in NPS pollution reduction from an economic perspective. This study provides a foundation for the implementation of Payment for Ecosystem Service(PES) and the prevention and control of NPS pollution.

Cost-Benefit Assessment of Inspection and Repair Planning for Ship Structures Considering Corrosion Model Uncertainty

Owing to high costs and unnecessary inspections necessitated by the traditional inspection planning for ship structures, the risk-based inspection and repair planning should be investigated for the most cost-effective inspection. This paper aims to propose a cost-benefit assessment model of risk-based inspection and repair planning for ship structures subjected to corrosion deterioration. Then, the benefit-cost ratio is taken to be an index for the selection of the optimal inspection and repair strategy. The planning problem is formulated as an optimization problem where the benefit-cost ratio for the expected lifetime is maximized with a constraint on the minimum acceptalbe reliability index. To account for the effect of corrosion model uncertainty on the cost-benefit assessment, two corrosion models, namgly, Paik＇ s model and Guedes Soares＇ model, are adopted for analysis. A numerical example is presented to illustrate the proposed method. Sensitivity studies are also providet. The results indicate that the proposed method of risk-based cost-benefit analysis can effectively integrate the economy with reliability of the inspection and repair planning. A balance can be achieved between the risk cost and total expected inspection and repair costs with the proposed method, which is very. effective in selecting the optimal inspection and repair strategy. It is pointed out that the corrosion model uncertainty and parametric uncertaintg have a significant impact on the cost-benefit assessment of inspection and repair planning.

Analysis of Satisfaction with Business Cost in Shanghai Using Structural Equation Modeling Approach

Tracing the origins of business cost, to define the satisfaction assessment factors on the business cost in Shanghai was investigated in this paper. Arguing that these effects: a single low cost is not only the criterion determining satisfaction. Other important factors, such as enterprise internal cognitive attitude,stability of the external environment,the quality of perceptions of government services can affect satisfaction. Within structural equation modeling( SEM) approach, six sets of hypotheses are drawn up and tested with a sample of 338 enterprises using questionnaires. Additionally,the analyses of findings introduce the crucial importance of these features in the assessment of satisfaction with business cost in Shanghai. Finally, the results show that internal cognitive has a positive impact on satisfaction. Stability of the external environment has a significant relationship with the effectiveness of government services. Stability of the external environmeat and the effectiveness of government servises have a positive effect on satisfaction.

Model of Cost-benefit Flow in Six Green Projects in China

From the point of cost-benefit flow and with the Six Green Projects in China as the case and background, it is criticized that the current natural resource and environmental management and the policies in China have some problems unsolved since the model of cost-benefit flow is still centralized and mainly in an administrative way in spite of many efforts made theoretically and practically. It is suggested that a new model based on market-oriented economy from the point of cost-benefit flow with Six Green Projects Management and Policies System consist of complete natural reserve (NR). Management system included environmental nature reserves in addition to biodiversity nature reserve, paid using nature resources, an environmental conservation and construction industry and renewable resource production incentive system that turn the direct administration and operation to management and services. The detail figure of the new model of cost-benefit flow is provided and the main points related are discussed in this paper.

An Integrated Rehabilitation Model: An Ideal Framework for Limiting Health Care Costs

The financial crisis has caused a severe limitation of resources for the public health service and rehabilitation. The proposal of integrated diagnosis and treatment in rehabilitation, involving the introduction of new therapeutic models alongside orthodox models, could lead to a reduction in health care costs through better patient compliance. In rehabilitative assistance in health care, the limiting of financial resources can be simplified, given its multifaceted nature and the need to integrate clinical experience with research. In addition, the phases of rehabilitative recovery do not focus on organ damage, but improved participation and the reduction of disability. For this reason, we have considered incorporating narrative based medicine (NBM) and Psycho-Neuro-Immuno-Endocrinology (PNEI) in the rehabilitation process through an empathetic approach, taking evidence based medicine (EBM) into account, thus creating a “framework” of reference. Managing patients through this “framework” would be a move towards an integrated model of care that could lead to a reduction in health care costs, given the aging population and the rise in patients with chronic pain. The decision to modify health care in rehabilitative assistance through a new “framework” will require time, organizational capacity and experimentation, but may represent the appropriate response for an improved quality of life for patients and a better allocation of resources.

Modeling Anthrax with Optimal Control and Cost Effectiveness Analysis

Anthrax is an infection caused by bacteria and it affects both human and animal populations. The disease can be categorized under zoonotic diseases and humans can contract infections through contact with infected animals, ingest contaminated dairy and animal products. In this paper, we developed a mathematical model for anthrax transmission dynamics in both human and animal populations with optimal control. The qualitative solution of the model behaviour was analyzed by determining Rhv, equilibrium points and sensitivity analysis. A vaccination class was incorporated into the model with waning immunity. Local and global stability of the model’s equilibria was found to be locally asymptotically stable whenever Rhv Rhv. It was revealed that reducing animal and human interaction rate, would decrease Rhv. We extended the model to optimal control in order to find the best control strategy in reducing anthrax infections. It showed that the effective strategy in combating the anthrax epidemics is vaccination of animals and prevention of humans.

Cost-benefit Analysis of Scale Pig Breeding in Shandong Province Based on Modified Entropy Weight-TOPSIS Model

According to the relevant statistical data in National Agricultural cost-benefit Data Compilation(2001- 2013),we use the modified entropy weight- TOPSIS model to research the cost-benefit status of scale pig breeding in Shandong Province from the perspective of comparing it with that of the entire country and 9 other main pig producing areas. The results show that compared with the national average,the cost-benefit ratio of small scale pig breeding in Shandong Province is lower,while the cost-benefit ratio of medium scale and large scale pig breeding is significantly improved; the cost-benefit ratio of small scale pig breeding in Shandong Province is basically the same as that in 9 other main pig producing areas,while the cost-benefit ratio of medium scale and large scale pig breeding is higher; the output value of main products and the purchase price of piglet are two major bottlenecks restricting the cost-benefit improvement of scale pig breeding in Shandong Province.