Applications of Evolutionary Computation: EvoApplications - download pdf or read online

By Fatma Corut Ergin, A. Şima Uyar, Ayşegül Yayimli (auth.), Cecilia Di Chio, Anthony Brabazon, Gianni A. Di Caro, Rolf Drechsler, Muddassar Farooq, Jörn Grahl, Gary Greenfield, Christian Prins, Juan Romero, Giovanni Squillero, Ernesto Tarantino, Andrea G. B

ISBN-10: 3642205194

ISBN-13: 9783642205194

ISBN-10: 3642205208

ISBN-13: 9783642205200

This publication constitutes the refereed lawsuits of the foreign convention at the functions of Evolutionary Computation, EvoApplications 2011, held in Torino, Italy, in April 2011 colocated with the Evo* 2011 occasions. because of the massive variety of submissions obtained, the court cases for EvoApplications 2011 are divided throughout volumes (LNCS 6624 and 6625). the current quantity comprises contributions for EvoCOMNET, EvoFIN, EvoIHOT, EvoMUSART, EvoSTIM, and EvoTRANSLOC. The fifty one revised complete papers awarded have been rigorously reviewed and chosen from quite a few submissions. This quantity provides an summary in regards to the most recent examine in EC. components the place evolutionary computation thoughts were utilized diversity from telecommunication networks to complicated structures, finance and economics, video games, photograph research, evolutionary tune and artwork, parameter optimization, scheduling, and logistics. those papers could provide guidance to assist new researchers tackling their very own challenge utilizing EC.

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Extra info for Applications of Evolutionary Computation: EvoApplications 2011: EvoCOMNET, EvoFIN, EvoHOT, EvoMUSART, EvoSTIM, and EvoTRANSLOG, Torino, Italy, April 27-29, 2011, Proceedings, Part II

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In the present work, we investigate the possibility of using a Genetic Algorithm (GA) [8] as a fast heuristic to widen the exploration of the discrete power solution space: the aim is to exploit the entire set of discrete power levels and thus to evaluate power configurations with levels not included in the best solutions found in [7]. In particular, our aim is to improve the capacity of solving large realistic instances by finding higher value solutions. We thus design a GA that takes into account the specific features of the PFMAP and we test its performance on the same set of realistic WiMAX instances used in [7].

8 2 Fig. 2. Continuous dependence of solutions on β for the simple 5-node network configuration used in Figure 1 The previous work shows that some of the principles and features gained from rigorous study of small networks are consistent with larger and more complicated networks that are much more difficult to analyze. In particular, for the simple 5-node network and a larger 50-node network, small routing exponents β 1 lead to stable, multi-route solutions whereas large exponents β 1 lead to stable single-route solutions.

The increment h2 is the amount of time between deployment of ants from a source node s. We assume that h1 ≤ h2 . The routing protocol can be described as follows: 1. N ants are released from the source node. The source node resets its clock to t = 0. 2. Each ant moves through the network following (1) and maintaining a nodevisited stack until it arrives at the destination node. 3. An ant reaching the destination node will retrace its steps back to the source. e. no node is visited twice), the ant deposits pheromone along the links it traverses.

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Applications of Evolutionary Computation: EvoApplications 2011: EvoCOMNET, EvoFIN, EvoHOT, EvoMUSART, EvoSTIM, and EvoTRANSLOG, Torino, Italy, April 27-29, 2011, Proceedings, Part II by Fatma Corut Ergin, A. Şima Uyar, Ayşegül Yayimli (auth.), Cecilia Di Chio, Anthony Brabazon, Gianni A. Di Caro, Rolf Drechsler, Muddassar Farooq, Jörn Grahl, Gary Greenfield, Christian Prins, Juan Romero, Giovanni Squillero, Ernesto Tarantino, Andrea G. B


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