Fuzzy Monte Carlo Simulation to Optimize Resource Planning and Operations

Abstract

Resources planning and operations are essential concerns and specialty areas within industrial engineering and project management. Crew configuration plays a significant role in resource planning and operations. Crew configuration inefficiency is one of the most common reasons for the low productivity of manpower. Resources planning contains some inherent uncertainties and risks because it is an estimate of unknown values. Many factors affect resource planning. Some of these factors are fuzzy variables such as expert's judgment, and some of them are random variables such as direct cost of equipment. The objective of this chapter is to present a method that combines fuzzy logic and Monte Carlo simulation (MCS) for the selection of the best crew configuration to perform a certain task. The model presented in this chapter is a joint propagation method based on both the probability theory of MCS and the possibility theory of fuzzy arithmetic. The research outcomes indicate that the presented model can reduce the duration and cost of a certain task, which will help reduce the cost and duration of the project.

A new fuzzy approach and bankruptcy theory in risk estimation in Waste Load Allocation

“…Nonetheless, efforts to improve them are being pursued by new methods; we can mention MCS integration with Fuzzy logic (e.g., Alzarrad 2020;Tabesh et al 2021).…”