Workshop on Parallel Techniques
in Search, Optimization, and Learning
Modern research during these last twenty years has expanded to address very interesting problems of large complexity (dimensionality, restrictions, computing intensive...). In particular, those coming from real-world scenarios are getting both larger in size and harder in complexity.
Aiming at finding accurate (and robust) solutions in the shortest possible computational time, these problems face researchers to new challenges of difficult solution with traditional techniques and computers. One way to achieve unseen numerical and efficient results is the use of parallel algorithms, hardware, and specialized techniques.
With the evolution of parallel architectures (symmetric multiprocessors, multi/many-cores, GPUs, etc.), many opportunities emerge for the design of efficient algorithms.
This workshop seeks contributions on new theoretical advances and carefully designed, well-analyzed proposals in the field of parallel search algorithms. It is also intended to gather researchers from several domains (operations research, computer science, management science, communications and networks, ...) with an opportunity for presenting and discussing their more recent developments in theory and application of parallel search algorithms. An open atmosphere for discussion of future research lines will hopefully help in defining where we are and where are we going in this crossroad between parallelism and (Nature) problem solving.
9:30 - 9:45: Opening, by Enrique Alba.
9:45 - 10:05: New Load Balancing Strategy for Solving Permutation Flow Shop Problem Using Grid Computing, by Samia Kouki, Talel Ladhari, and, Mohamed Jemni.
10:05 - 10:25: Computing UIO Sequences Using Parallel GAs, by Qiang Guo, John McCall and Horacio González-Vélez.
10:25 - 10:45: Parallel Local Elimination Algorithms for Sparse Discrete Optimization Problems, by Daria Lemtyuzhnikova and Oleg Shcherbina.
10:45 - 11:15: Coffee break
11:15 - 11:35: Grid Computing Systems and Combinatorial Optimization, by Oleg Shcherbina and Eugene Levner.
11:35 - 11:55: Using Pool-based Evolutionary Algorithms for Scalable and Asynchronous Distributed computing, by J.J. Merelo, A.M. Mora, C. M. Fernandes, M. G. Arenas, and Anna I. Esparcia-Alcazar
11:55 - 12:15: Using Theory for Designing Competitive Distributed EAs, by K. Osorio, G. Luque, E. Alba
12:15 - 12:45: Round-table meeting.
12:45 - 13:00: Closing.
Extended Abstract Submission: June 8th, 2012
Author Notification: June 18th, 2012
Conference: September 1-5, 2012
Researchers are invited to submit extended abstracts of no more than 4 pages using the LNCS style (see Information for LNCS Authors). The contributions should be submitted as PDF by email to Francisco Luna (flv@lcc.uma.es) and Enrique Alba (eat@lcc.uma.es).
In order to promote discussion among the participants, the workshop will consist of short oral presentations (no more than 10-15 minutes) plus a one-hour final discussion on several hot topics that will be gathered before and during the workshop celebration. Contributing authors will be asked to send their proposals that might be related or not to their extended abstract. Relevant research topics that will surely arise during the workshops will be considered as well. Following the tradition of PPSN, the workshop abstracts are not published in the conference proceedings.
Works are expected (but not limited) in the following areas:
Parallel evolutionary algorithms Parallel metaheuristics Master/slave model Massively parallel algorithms for GPUs SIMD/MIMD and FPGA parallelization Parallel evolutionary algorithms Parallel metaheuristics Master/slave model Massively parallel algorithms for GPUs SIMD/MIMD and FPGA parallelization Parallel algorithms for shared and distributed memory architectures Multicore execution of parallel algorithms Parallel algorithms for clusters Grid and cloud computing P2P algorithms Theoretical models of parallel methods Design of benchmarks for parallel algorithms Parallel hybrid/memetic algorithms Parallel algorithms for dynamic optimization Parallel competitive/cooperative algorithms and agents Parallel platforms (clusters, multi-core, many-core, GPUs, etc.) Statistical assesment of parallel algorithms Real-world applications on engineering, bioinformatics, telecommunications, etc.
Enrique Alba, University of Malaga, Spain (eat@lcc.uma.es)
Francisco Luna, University of Malaga, Spain (flv@lcc.uma.es)