Abstract

Chance Constrained Programming (CCP) as one of the special parts of mathematical programming in which its application in industrial and academic fields is currently needed to cover the problem of uncertainty in making decisions. The CCP technique is an efficient and easy tool to apply for data involved to random parameters by assuming random parameters must follow a stable normal distribution. In selection process, budget goal, making the most benefits, and achieving minimum travel are considered as a random parameter and solved by using CCP. Goal Programming (GP) model, will be used to model the rail system transportation project selection process, because allocating resources into all projects at the same time requires multi-criteria decision making techniques.

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