The complexity and dynamics of the executive projects have coped contractors with substantial hazards and losses. Project risk management is a critical tool for authority to improve its performance and secure the success of the organization. However, a number of standards and approaches have been developed to formulate the projects based on their risks. The Elena guideline is a systematic standard developed by Iran Project Management Association. This guideline provides the full cycle of the risk management process. Risk evaluation is the key part of the risk management process. On the other hand, different techniques have been developed to model a risk evaluation problem. Fuzzy inference system is one of the most popular techniques that is capable of handling all types of the uncertainty involved in projects. This paper proposes a three-stage approach based on the fuzzy inference system under the environment of the Elena guideline to cope with the risky projects. Finally, an illustrative example of the risk evaluation is presented to demonstrate the potential application of the proposed model. The results show that the proposed model evaluates the risky projects efficiently and effectively.

In this study, the problem of scheduling jobs on unrelated parallel machines with sequence-dependent setup times under due-date constraints is considered to minimize the total cost of tardiness and earliness. A new mathematical model is presented for considered problem and due to the complexity of the problem; an integrated meta-heuristic algorithm is designed to solve the problem. The proposed algorithm consists of genetic algorithm as the basic algorithm and simulated annealing method as local search procedure that follows the genetic algorithm to improve the quality of solutions. The performance of the proposed algorithm is evaluated by solving a set of test problems. The results show that the proposed integrated algorithm is effective.

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