Distributed and Guided Genetic Algorithm for Humanitarian Relief Planning in Disaster Case
In this paper we propose a distributed and guided genetic algorithm for humanitarian relief planning in natural disaster case. It is a dynamic vehicle routing problem with time windows (DVRPTW), where customers should be served during a given time interval. This problem is an extension of classic vehicle routing problem. In the case of a disaster, emergency planning must be fast, consistent and scalable. For these reasons we opted for an improved genetic algorithm by adding some sort of guide to accelerate the convergence of the algorithm. Thus, the genetic algorithm can provide a population of solutions that can address the dynamic aspect of the problem. The objective of our approach is to provide a plan to meet all the demands with minimizing the total distance travelled. The proposed approach has been tested with theoretical data and showed high efficiency, which infers the possibility of applying for the management of emergency calls in the event of major disaster.
KeywordsDisaster planning Disaster logistics Vehicle routing problem with time windows Dynamic VRP Disaster relief Discrete optimization Multi-agents solving problem
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- [Go]Goldberg, D.: Genetic algorithms in search, optimization, and machine learning. Advison-Wesley (1989)Google Scholar
- [Ho]Hong, L.: An improved lns algorithm for real-time vehicle routing problem with time windows. Computers and Operations Research (2011)Google Scholar
- [MZGB2]Mguis, F., Zidi, K., Ghedira, K., Borne, P.: Distributed approach for vehicle routing problem in disaster case. In: 13th IFAC Symposium on Control in Transportation Systems, Sofia-Bulgaria (2012a)Google Scholar
- [MZGB1]Mguis, F., Zidi, K., Ghedira, K., Borne, P.: Modélisation d’un système multi-agent pour la résolution d’un problme de tournées de véhicules dans une situation d’urgence. In: 9ème Conférence Internationale de Modélisation, Optimisation et SIMulation, MOSIM 2012, Bordeaux, France (2012b)Google Scholar
- [ZZ]Zeddini, B., Zargayouna, M.: Auto-organisation spatio-temporelle pour le vrptw dynamique. RJCIA (2009)Google Scholar
- [Zi]Zidi, K.: Systme Interactif d’Aide au Dplacement Multimodal. PhD thesis, Ecole centrale de Lille France (2006)Google Scholar
- [ZMGB]Zidi, K., Mguis, F., Ghedira, K., Borne, P.: Distributed genetic algorithm for disaster relief planning. Int. J. Comput. Commun. 8(5), 769–783 (2013)Google Scholar