ملخص للطرق المستخدمة في تحديد و حل المخاطر في المشاريع الهندسية
Techniques of risk analysis in construction projects include risk premium, risk adjusted discount rate, subjective probability, decision analysis, sensitivity analysis, Monte Carlo simulation, stochastic dominance, Caspar and intuition (Raftery, 1994 and Williams and Heims, 1989). Methods of decision analysis are algorithms, mean end analysis, bayesian theory and decision trees. These provide decision-making tools in an uncertain environment. An algorithm contains a sequence of instructions for problem solving. Mean end analysis is a method of clarifying a chain of objectives to identify a series of decision points(Alkintoye and Macleod, 1997). The decision tree shows sequence of known choices (a number of alternatives) and their possible outcomes graphically in a tree form such that the decision maker can identify best alternatives that achieve the objectives of a major project. The decision tree method is useful in deciding methods of construction, choosing alternative projects, and in contractual problems such as whether to proceed with a claim and assessing the likelihood of a claim succeeding (Thompson and Perry, 1979). Monte Carlo analysis is a form of stochastic simulation. Using this method the probability of project outcome is obtained by carrying out a number of iterations, depending on the degree of confidence required. Probability theory considers all uncertainty random, however, not all types of uncertainty are random. A great deal of management issues in construction does not comply with randomness properties. They are mainly cognitive and thus do not lend themselves to precise measurement (Alkintoye and Macleod, 1997). Caspar is a computer aided simulation for project appraisal and review. It is a project management tool designed to model the interaction of time, resources, cost and revenue throughout the entire life of a project and it has capacity to evaluate the consequences of factors such as delay and inflation, and changes to the market or to production rates. Such computer-based methods recognize the dynamic project environment(Alkintoye and Macleod, 1997). The use of traditional methods which assess risk involved in projects in a deterministic way has been criticized for failing to take into account the sequential nature of construction management process(Huseby and Skogen, 1992).