A stochastic predictive control approach to project risk management

This work shows a control policy based on MPC and applied to project risk management. MPC has been applied due the properties that presents such as the easy constraint treatment or the extension to multivariable case. The control actions are the mitigation actions to execute in order to reduce the risk exposure. Stochastic variables have been introduced to model the uncertainties of risk impacts. Integer variables are involved in the optimization problem modelling the mitigation actions

Hybrid algorithm for scheduling and risk assessment of projects

IFAC CONFERENCE ON ANALYSIS AND DESIGN OF HYBRID SYSTEMS (.2003.SAINT-MALO BRITTANY, FRANCIA)This work presents a technique for optimal scheduling of projects in terms of time and cost, taking into account risk assessment. Tasks are characterized by p-timed Petri nets, where places have assigned an execution time. The proposed technique minimizes the time execution and the cost of the whole project taking into account the Petri nets describing the tasks and the project risk assessment plan. The risk mitigation is carried on through actions where variables that model them may be discrete or continuousMinisterio de Ciencia y Tecnología DPI200 1-2380-C02-0

A bi-objective genetic algorithm approach to risk mitigation in project scheduling

A problem of risk mitigation in project scheduling is formulated as a bi-objective optimization problem, where the expected makespan and the expected total cost are both to be minimized. The expected total cost is the sum of four cost components: overhead cost, activity execution cost, cost of reducing risks and penalty cost for tardiness. Risks for activities are predefined. For each risk at an activity, various levels are defined, which correspond to the results of different preventive measures. Only those risks with a probable impact on the duration of the related activity are considered here. Impacts of risks are not only accounted for through the expected makespan but are also translated into cost and thus have an impact on the expected total cost. An MIP model and a heuristic solution approach based on genetic algorithms (GAs) is proposed. The experiments conducted indicate that GAs provide a fast and effective solution approach to the problem. For smaller problems, the results obtained by the GA are very good. For larger problems, there is room for improvement

Involving External Stakeholders in Project Courses

Problem: The involvement of external stakeholders in capstone projects and project courses is desirable due to its potential positive effects on the students. Capstone projects particularly profit from the inclusion of an industrial partner to make the project relevant and help students acquire professional skills. In addition, an increasing push towards education that is aligned with industry and incorporates industrial partners can be observed. However, the involvement of external stakeholders in teaching moments can create friction and could, in the worst case, lead to frustration of all involved parties. Contribution: We developed a model that allows analysing the involvement of external stakeholders in university courses both in a retrospective fashion, to gain insights from past course instances, and in a constructive fashion, to plan the involvement of external stakeholders. Key Concepts: The conceptual model and the accompanying guideline guide the teachers in their analysis of stakeholder involvement. The model is comprised of several activities (define, execute, and evaluate the collaboration). The guideline provides questions that the teachers should answer for each of these activities. In the constructive use, the model allows teachers to define an action plan based on an analysis of potential stakeholders and the pedagogical objectives. In the retrospective use, the model allows teachers to identify issues that appeared during the project and their underlying causes. Drawing from ideas of the reflective practitioner, the model contains an emphasis on reflection and interpretation of the observations made by the teacher and other groups involved in the courses. Key Lessons: Applying the model retrospectively to a total of eight courses shows that it is possible to reveal hitherto implicit risks and assumptions and to gain a better insight into the interaction...Comment: Abstract shortened since arxiv.org limits length of abstracts. See paper/pdf for full abstract. Paper is forthcoming, accepted August 2017. Arxiv version 2 corrects misspelled author nam

Enterprise Risk Management In The Oil And Gas Industry: An Analysis Of Selected Fortune 500 Oil And Gas Companies Reaction In 2009 And 2010

In 2009, four of the top ten Fortune 500 companies were classified within the oil and gas industry. Organizations of this size typically have an advanced Enterprise Risk Management system in place to mitigate risk and to achieve their corporations\u27 objectives. The companies and the article utilize the Enterprise Risk Management Integrated Framework developed by the Committee of Sponsoring Organizations (COSO) as a guide to organize their risk management and reporting. The authors used the framework to analyze reporting years 2009 and 2010 for Fortune 500 oil and gas companies. After gathering and examining information from 2009 and 2010 annual reports, 10-K filings, and proxy statements, the article examines how the selected companies are implementing requirements identified in the previously mentioned publications. Each section examines the companies Enterprise Risk Management system, risk appetite, and any other notable information regarding risk management. One observation was the existence or non-existence of a Chief Risk Officer or other Senior Level Manager in charge of risk management. Other observations included identified risks, such as changes in economic, regulatory, and political environments in the different countries where the corporations do business. Still others identify risks, such as increases in certain costs that exceed natural inflation, volatility and instability of market conditions. Fortune 500 oil and gas companies included in this analysis are ExxonMobil, Chevron, ConocoPhillips, Baker Hughes, Valero Energy, and Frontier Oil Corporation. An analysis revealed a sophisticated understanding and reporting of many types of risks, including those associated with increasing production capacity. Specific risks identified by companies included start-up timing, operational outages, weather events, regulatory changes, geo-political and cyber security risks, among others. Mitigation efforts included portfolio management and financial strength. There is evidence that companies in later reports (2013) are more comprehensive in their risk management and reports as evidenced by their 10-K and Proxy Statements (Marathon Oil Corporation, 2013)

Project Risk Management Phases

Risk management is the human activity which integrates recognition of risk, risk assessment, developing strategies to manage it, and mitigation of risk using managerial resources. Notwithstanding the domain of activities where they are conducted, projects often entail risks, and risk management has been widely recognized as a success factor in project management. Following a concept clarification on project risk management, this paper presents a generic list steps in the risk management process. Risk analysis is highlighted. I use expected value analysis for quantitative estimation. I propose to determine risk probability using Fishbone-Ishikawa diagrams and I provide an example that illustrates this theory.risk evaluation, project management, risk management, expected value analysis..