# A Comprehensive Methodology for Investment Project Assessment Based on Monte Carlo Simulation
## 1 Introduction  
Investment decision-making is a process with long-term effects on a company's economy. The investments in real capital are especially one of the essential activities in ensuring the competitiveness of the company in the long term. The profitability of investment projects is affected by many factors. Therefore, the project evaluation process should incorporate all factors that possibly influence its value [1, 2]. Financial investments are one of the ways in which a company can invest its finances. Many research works have dealt with this issue. Reference [3] established a deterministic equivalent income model based on risk cost and risk aversion of investors. The model fully considered subjective and objective factors affecting risk investment and reasonably evaluated risk investment schemes. In [4], authors developed a general framework for analysing corporate investment risk management and financing policies. In [5], financial risks were divided into three types (environment, resource-allocation, stakeholder-cooperation risk), which created a three-dimensional financial risk system. A methodology for streamlining a company's investment activities to solve financial risk using the Monte Carlo method was presented by [6]. On the other hand, real investments are crucial for manufacturing companies. In a competitive market, manufacturing companies must utilize their available capacity efficiently to obtain high profits. Ref. [7] presented efficient approaches to find an optimal product mix for the company to achieve optimal manufacturing. The most important decisions made in production systems concern the determination of the product mix in such a way as to obtain maximum throughput. Researchers [8] discussed the inefficiency of the traditional theory of constraints algorithm in handling the multiple bottleneck problem. Production plan optimization in connection with investment decision-making was presented by [9]. A framework for conductingthe economic analysis and identifying the most suitable methodology before proceeding with the investment was proposed in [10]. In general, investment activity is characterized by high risk and uncertainty. Many investment project failures are due to scale-up issues and uncertain estimations of the capital and production costs. Decision-making strategies and risk assessment modelling are crucial to decrease the risks of losing large investment projects [11]. The literature sources introduce many review papers and case studies on corporate investments and investment risks in various industrial fields. In the oil and gas industry, ref. [12] presented background on the use of risk analysis methods and carried out Monte Carlo simulation to predict a cumulative distribution function for well drilling. In the paper by [13], a probabilistic hesitant fuzzy set was used for handling uncertainty in multiple attribute decision-making. Authors of [14] identified a link between cash flow risk, capital structure decisions, and operating cash flows. Ref. [15] presented a methodology that uses the Monte Carlo Method to estimate economic parameters, which may help a decision, considering the risk in project sustainability. Ref. [16] dealt with introducing a Monte Carlo Simulation approach to risk analysis, based on a life-cycle representation of renewable energy technology investment projects. Authors of [17] presented a computer-based model for cash flow forecasting and for studying the impact of risk factors on cash flow. In investment decision-making, an important role is played not only by the analysis and assessment of investment risks but also by choosing the optimal investment variant with respect to the risk (in the case of financial investments) and the optimal use of production capacities taking the risk into account (in the real investment case). Optimization in investment decision-making is the subject of other research papers.