PERMS: An efficient rescue route planning system in disasters
نویسندگان
چکیده
The occurrence of natural and man-made disasters usually leads to significant social economic disruption, as well high numbers casualties. Such occurrences are difficult predict due the huge number parameters with mutual interdependencies which need be investigated provide reliable predictive capabilities. In this work, we present high-Performance Emergent Rescue Management e-System ( PERMS ), an efficient rescue route planning scheme operating within a high-performance emergent management system for vehicles based on mobile cloud computing paradigm. More specifically, emergency problem (ERRP) is multiple travelling salesman (MTSP), novel phased heuristic scheme. This consists obstacle constraints task equal division-based K-means++ clustering algorithm (OT-K-means++), more suitable victims in disaster environments, glow-worm swarm optimisation chaotic initialisation (GSOCI), provides appropriate each vehicle. A prototype developed evaluate performance proposed approach, demonstrates better compared other well-known widely used algorithms. As demonstrated by validation process, our approach enhances accuracy convergence speed solving problem. Furthermore, it shortens length route, time, reasonable balanced allocation tasks, whilst achieving overall process. considering scenarios 200 victims, K-means K-means++, OT-K-means++ reduces time cost 9.52% 17.39% respectively, iterations 11.11% 15.78% respectively. Compared ACO or GA, GSOCI 9.81% 16.36% 4.35% 15.38% • proposed. Implementation Clustering improved algorithm. Glow-worm vehicles. Chebyshev mappings C2Opt improving quality speed.
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ژورنال
عنوان ژورنال: Applied Soft Computing
سال: 2021
ISSN: ['1568-4946', '1872-9681']
DOI: https://doi.org/10.1016/j.asoc.2021.107667