You are provided with the abstract of a scientific paper and the abstracts of the papers it references. Your task is to write a Related Work section for the main paper. This section should concisely summarize and integrate the key points from the cited abstracts, reflecting how they relate to the main paper's contributions and context. In your summary, use numerical citation markers like [1], [2], etc., to refer to the corresponding papers.

Main Abstract:
Emergency evacuation is the process of movement of people away from the threat or actual occurrence of hazards such as natural disasters, terrorist attacks, fires and bombs. In this paper, we focus on evacuation from a building, but the ideas can be applied to city and region evacuation. We define the problem and show how it can be modeled using graphs. The resulting optimization problem can be formulated as an integer linear program. Though this can be solved exactly, this approach does not scale well for graphs with thousands of nodes and several hundred thousands of edges. This is impractical for large graphs. We study a special case of this problem, where there is only a single source and a single sink. For this case, we give an improved algorithm , whose evacuation time is always at most that of a famous algorithm , and whose running time is strictly less than that of CCRP. We prove this mathematically and give supporting results by extensive experiments. We also study randomized behavior model of people and give some interesting results.

Cited Abstract(s):
[1]: Evacuation planning is of critical importance for civil authorities to prepare for natural disasters, but efficient evacuation planning in large city is computationally challenging due to the large number of evacuees and the huge size of transportation networks. One recently proposed algorithm Capacity Constrained Route Planner (CCRP) can give sub-optimal solution with good accuracy in less time and use less memory compared to previous approaches. However, it still can not scale to large networks. In this paper, we analyze the overhead of CCRP and come to a new heuristic CCRP++ that scalable to large network. Our algorithm can reuse search results in previous iterations and avoid the repetitive global shortest path expansion in CCRP. We conducted extensive experiments with real world road networks and different evacuation parameter settings. The result shows it can gives great speed-up without loosing the optimality.
To overcome the unnecessary expansion in each iteration, [1] introduced the CCRP++ algorithm. The main advantage of CCRP++ is that it runs faster than CCRP. But the quality of solution is not good, because availability along a path may change between the times when paths are reserved and when they are actually used.