Sustainable urban infrastructure
A. Edrisi; A. Nadi; M. Askari
Abstract
BACKGROUND AND OBJECTIVES: After having struck in a major natural disaster like an earthquake, different organizations run about to decrease losses. The lack of accurate demand information is a common problem that all emergency response organizations have to encounter such a crisis. Evaluation of ...
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BACKGROUND AND OBJECTIVES: After having struck in a major natural disaster like an earthquake, different organizations run about to decrease losses. The lack of accurate demand information is a common problem that all emergency response organizations have to encounter such a crisis. Evaluation of the City disaster level is a mean to feed this information to the disaster response operations. The objective of this research is eschedule a group of experts to assess relief demand. These evaluation teams need to be scheduled to minimize the evaluation time. METHODS: This paper aims to formulate the routing and scheduling of the assessment teams so that real demand information for savings and rescue would be available as soon as possible. The simulated annealing algorithm is used to solve the scheduling problem. FINDING: two cost functions, sum of arrival time and max completion time, were evaluated. The latest is found to perform better in evaluation of the teams performance. CONCLUSION:The performance of the approach is tested on several randomly generated networks and synthesized demand data. The results show a 13 % improvement in the total completion time of operation in comparison with previous approaches.
Sustainable urban infrastructure
A. Edrisi; M. Askari
Abstract
Most cities around the world are in danger of disasters. Among disasters, the earthquake is the most dangerous and ruining one. Iran has been located in the Alpine-Himalayas seismic belt, and because of the significant frequency of severe earthquakes happening all over the country compare to other countries ...
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Most cities around the world are in danger of disasters. Among disasters, the earthquake is the most dangerous and ruining one. Iran has been located in the Alpine-Himalayas seismic belt, and because of the significant frequency of severe earthquakes happening all over the country compare to other countries and the state of the unsecured residential and non-residential buildings in most of the areas, attention to the post-disaster phase is vital. This study aims to locate shelters in some districts and allocate at-risk people of all districts to these shelters. Also, another purpose of this study is the reduction of the allocated budget by the government and reduction of traveled distance by people considering the possibility of link failure due to the earthquake. Allocated budget by the government for shelter construction includes the fixed and marginal cost. Mixed Integer Linear Programming has been used for modeling the suggested method. This method has been applied to the Tehran network, and the Genetic Algorithm has been used for solving the proposed method. The results showed that the leading share of the imposed costs arose from the shelter construction budget. Furthermore, the probability of choosing a district for constructing a shelter has a direct relationship with the at-risk population and the cost of shelter construction in that district. Seven districts have chosen to build shelters with about 400 thousand people capacity. District 16 chosen for constructing the biggest shelter that should serve to up to 123 thousand people and District 5 chosen to construct the smallest shelter that should serve to up to 16 thousand people.
