This paper presents a new multi-objective model for a vehicle routing problem under a stochastic uncertainty. It considers traffic point as an inflection point to deal with the arrival time of vehicles. It aims to minimize the total transportation cost, traffic pollution, customer dissatisfaction and maximizes the reliability of vehicles. Moreover, resiliency factors are included in the model to increase the flexibility of the system and decrease the possible losses that may impose on the system. Due to the NP-hardness of the presented model, a meta-heuristic algorithm, namely Simulated Annealing (SA) is developed. Furthermore, a number of sensitivity analyses are provided to validate the effectiveness of the proposed model. Lastly, the foregoing meta-heuristic is compared with GAMS, in which the computational results demonstrate an acceptable performance of the proposed SA.

In the current world, all human beings are forced to work for the living to provide their living requirements. Meeting these needs faced human with numerous psychological problems. One of the psychological problems of humanity in the current world is associated with stress caused by working conditions that human are daily forced to face with them. Finding the right solution for management of unconventional stress requires understanding the capabilities of individuals and strategies to face with them in stressful situations. This paper presents a survey to study the quality of working life and social support by considering the mediating role of resiliency. The study has accomplished among all 215 environmental guards of Mazandaran province, Iran. The results of this survey indicate that enhancing the social support of environmental guards by the relevant institutions especially communication and supporting them by friends played an important role for increasing their resilience.

Energy crisis in recent decades has demonstrated strong interdependence between national security and energy security. We are also witness of sever conflicts in oil-rich zones such as Middle-East and West of Suez. This study is the first attempt to provide a flexible multi-objective mathematical model which not only mitigates catastrophic risks by filtering and taking plausible oil-supply disruption scenarios into account, but also reduces oil-supply disruption probability by considering and optimizing political, economic and financial dimensions of oil procurement. Mentioned model determines a resilient portfolio of oil suppliers under each scenario and decides which ports or pipelines must be prepared for receiving oil. Furthermore, the proposed model in the second phase enhances oil-availability in crisis time by storing strategic oil stocks in appropriate geographic points. Also regarding to complexity of the second phase model, a meta-heuristic algorithm has been provided to solve the mentioned model. Finally validity of proposed model is checked by solving it for Greece case problem; sensitivity analysis shows that provided model significantly mitigates catastrophic risks threating energy security by balancing political affairs and reinforcing infrastructural facilities with the least possible cost.