Avi Ostfeld

Avi Ostfeld, D.Sc., P.E., D.WRE (www.technion.ac.il/~avi/avi.htm) is an Associate Professor at the Faculty of Civil and Environmental Engineering at the Technion – Israel Institute of Technology, and the Editor in Chief of the Journal of Water Resources Planning and Management Division, ASCE. Dr. Ostfeld was a Senior Engineer and Project Manager at TAHAL – Consulting Engineers Ltd. in Tel – Aviv from 1997 to 2000; a Research Associate at the Department of Civil Engineering, the University of Arizona, Tucson, AZ, from 1996 to 1997; and a Research Associate at the Technion Water Research Institute from 1994 to 1996. During 2008/2009 he spent sabbaticals as Visiting Professor at the University of Illinois at Urbana Champaign and at the University of Kyoto. Dr. Ostfeld research activities are in the fields of water resources systems, hydrology, and in particular in the area of water distribution systems optimization using evolutionary computation: water distribution systems security, optimal design and operation of water distribution systems, and integrating water quality and reliability into water distribution systems management and control.

2books edited

1chapters authored

Latest work with IntechOpen by Avi Ostfeld

Ants communicate information by leaving pheromone tracks. A moving ant leaves, in varying quantities, some pheromone on the ground to mark its way. While an isolated ant moves essentially at random, an ant encountering a previously laid trail is able to detect it and decide with high probability to follow it, thus reinforcing the track with its own pheromone. The collective behavior that emerges is thus a positive feedback: where the more the ants following a track, the more attractive that track becomes for being followed; thus the probability with which an ant chooses a path increases with the number of ants that previously chose the same path. This elementary ant's behavior inspired the development of ant colony optimization by Marco Dorigo in 1992, constructing a meta-heuristic stochastic combinatorial computational methodology belonging to a family of related meta-heuristic methods such as simulated annealing, Tabu search and genetic algorithms. This book covers in twenty chapters state of the art methods and applications of utilizing ant colony optimization algorithms. New methods and theory such as multi colony ant algorithm based upon a new pheromone arithmetic crossover and a repulsive operator, new findings on ant colony convergence, and a diversity of engineering and science applications from transportation, water resources, electrical and computer science disciplines are presented.

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