Theory and Practice of Uncertain Programming
Theory and Practice of Uncertain Programming
Robust source-adaptive real-time video transport over wireless multihop networks
International Journal of Wireless and Mobile Computing
Real-time traffic routing over a multilayered satellite architecture
International Journal of Wireless and Mobile Computing
Improved genetic algorithm for optimal design of fuzzy classifier
International Journal of Computer Applications in Technology
International Journal of Wireless and Mobile Computing
International Journal of Bio-Inspired Computation
Differential evolution and threshold accepting hybrid algorithm for unconstrained optimisation
International Journal of Bio-Inspired Computation
Scheduling optimisation for supply chain in networked manufacturing
International Journal of Computer Applications in Technology
International Journal of Bio-Inspired Computation
Multi-document summarisation using genetic algorithm-based sentence extraction
International Journal of Computer Applications in Technology
Application of interval type-2 fuzzy neural networks to predict short-term traffic flow
International Journal of Computer Applications in Technology
A new approach for integrating process planning with scheduling
International Journal of Computer Applications in Technology
International Journal of Computer Applications in Technology
Some practical solutions to the uncertainties of the ant colony optimisation
International Journal of Computer Applications in Technology
International Journal of Computing Science and Mathematics
Study on urban three-lane mixed traffic flow with buses based on the Nagel-Schreckenberg model
International Journal of Wireless and Mobile Computing
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After a sudden public event, how to optimise emergency evacuation routings and enhance the response capability of emergency system is an important issue for emergency management agency. In this paper, we choose the optimal evacuation routing under fuzzy environment to make sure the injured reach the destination safely and quickly. Chance-constrained programming model of emergency evacuation routings and chance-dependent constraint programming models are setup respectively and a hybrid intelligence algorithm is designed to solve the model. The algorithm, which combines simulation technique and the genetic algorithm, produces chromosomes according to priority-based coding mode, uses simulation technique to calculate target values of chromosomes, produces a new group by using improved roulette wheel method to select chromosomes, crosses by adopting the partially matched crossover method, and uses reciprocal exchange mutation method to mutate. Finally, an example is presented to validate the feasibility of this model and the algorithm. The research result can help emergency decision-makers to find an optimal route after a sudden public event and reduce the casualties caused by transportation delays.