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</o:shapelayout></xml><![endif]--></head><body lang=EN-GB link=blue vlink=purple><div class=WordSection1><p class=MsoPlainText>[Please circulate to all those who might be interested, and accept our apologies if you received multiple copies of this announcement]<o:p></o:p></p><p class=MsoPlainText><o:p> </o:p></p><p class=MsoPlainText>--------------------------------------------------------------------------<o:p></o:p></p><p class=MsoPlainText>CALL FOR ABSTRACTS<o:p></o:p></p><p class=MsoPlainText>Submission deadline: June 1, 2014<o:p></o:p></p><p class=MsoPlainText><o:p> </o:p></p><p class=MsoPlainText>Workshop on<o:p></o:p></p><p class=MsoPlainText>Scaling Behaviours of Landscapes, Parameters and Algorithms<o:p></o:p></p><p class=MsoPlainText><o:p> </o:p></p><p class=MsoPlainText>13th International Conference on Parallel Problem Solving from Nature <o:p></o:p></p><p class=MsoPlainText><o:p> </o:p></p><p class=MsoPlainText>PPSN 2014<o:p></o:p></p><p class=MsoPlainText><o:p> </o:p></p><p class=MsoPlainText><a href="http://ppsn2014.ijs.si/?show=workshops#ws4">http://ppsn2014.ijs.si/?show=workshops#ws4</a><o:p></o:p></p><p class=MsoPlainText><o:p> </o:p></p><p class=MsoPlainText>Ljubljana, Slovenia<o:p></o:p></p><p class=MsoPlainText><o:p> </o:p></p><p class=MsoPlainText>September 13, 2014<o:p></o:p></p><p class=MsoPlainText>--------------------------------------------------------------------------<o:p></o:p></p><p class=MsoPlainText><o:p> </o:p></p><p class=MsoPlainText>All too often heuristics and meta-heuristics for combinatorial optimisation problems require significant parameter tuning to work most effectively. Often this tuning is performed without any a priori knowledge as to how good values of parameters might depend on features of the problem. This lack of knowledge can lead to lot of computational effort and also has the danger of being limited to only problem instances that are similar to those that have been seen before. The aim of the workshop is to support the development of methods to give deeper insight into problem classes, and how to obtain and exploit structural information. <span style='color:#1F497D'><o:p></o:p></span></p><p class=MsoPlainText><span style='font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D'><o:p> </o:p></span></p><p class=MsoPlainText>The target participants will be those that:<o:p></o:p></p><p class=MsoPlainText>- work on the theory of search algorithms, but are seeking ways for the theory to have a practical impact;<span style='color:#1F497D'><o:p></o:p></span></p><p class=MsoPlainText>- work on direct applications, but are frustrated with the trial-and-error approaches that often are often used, and would like to bring 'theoretically-inspired methods' into their work;<span style='color:#1F497D'><o:p></o:p></span></p><p class=MsoPlainText>- work on flexible frameworks supporting interchangeability and reusability of components and a closer integration between parameter selection and the algorithm.<o:p></o:p></p><p class=MsoPlainText><o:p> </o:p></p><p class=MsoPlainText>Topics of interest include (but are not limited to):<o:p></o:p></p><p class=MsoPlainText>· (automated) parameter tuning/control in (meta)heuristics<o:p></o:p></p><p class=MsoPlainText>· (meta)heuristics for combinatorial optimisation, dynamic environments, multi-objective, discrete and continuous optimisation<o:p></o:p></p><p class=MsoPlainText>· (meta)heuristics to generate (create) heuristics (e.g., generation hyper-heuristics)<o:p></o:p></p><p class=MsoPlainText>· (meta)heuristics to choose heuristics (e.g., selection hyper-heuristics)<o:p></o:p></p><p class=MsoPlainText>· self adaptive (meta)heuristics<o:p></o:p></p><p class=MsoPlainText>· (meta)heuristics exploiting techniques, such as machine learning, data mining, statistical analysis or analytics<o:p></o:p></p><p class=MsoPlainText>· hybrids of (meta)heuristics with exact methods, such as mathematical or constraint programming<o:p></o:p></p><p class=MsoPlainText>· software tools (e.g., ECJ, HeuristicLab, HyFlex, Hyperion, jMetal, ParadisEO)<o:p></o:p></p><p class=MsoPlainText>· distributed/parallel frameworks<o:p></o:p></p><p class=MsoPlainText>· applications of metaheuristics to new challenging domains<o:p></o:p></p><p class=MsoPlainText>· analytical or semi-empirical studies of (meta)heuristics (e.g., landscape analysis)<o:p></o:p></p><p class=MsoPlainText>· performance prediction, performance robustness and scalability issues<o:p></o:p></p><p class=MsoPlainText>· barriers to uptake of (meta)heuristics in industry<o:p></o:p></p><p class=MsoPlainText><o:p> </o:p></p><p class=MsoPlainText>SUBMISSIONS<o:p></o:p></p><p class=MsoPlainText>-------------------<o:p></o:p></p><p class=MsoPlainText>We invite submissions as (extended) abstracts of 1-3 pages without exceeding 1000 words in Springer's LNCS style. The abstracts should be submitted in PDF format directly to the workshop organisers (see their emails copied below) and please mention “PPSN2014 workshop submission” in the subject line.<o:p></o:p></p><p class=MsoPlainText><o:p> </o:p></p><p class=MsoPlainText>All accepted papers presented at the workshop will be provided online from the workshop website.<o:p></o:p></p><p class=MsoPlainText><o:p> </o:p></p><p class=MsoPlainText>Submission deadline: June 1, 2014<o:p></o:p></p><p class=MsoPlainText><o:p> </o:p></p><p class=MsoPlainText>ORGANISERS<o:p></o:p></p><p class=MsoPlainText>-------------------<o:p></o:p></p><p class=MsoPlainText>Ender Ozcan and Andrew J. Parkes<o:p></o:p></p><p class=MsoPlainText><o:p> </o:p></p><p class=MsoPlainText>{ender.ozcan, andrew.parkes} [AT] nottingham.ac.uk<o:p></o:p></p><p class=MsoPlainText><o:p> </o:p></p><p class=MsoPlainText>Automated Scheduling, Optimisation and Planning (ASAP) Research Group<o:p></o:p></p><p class=MsoPlainText>School of Computer Science<o:p></o:p></p><p class=MsoPlainText>University of Nottingham<o:p></o:p></p><p class=MsoPlainText><o:p> </o:p></p><p class=MsoNormal><o:p> </o:p></p></div></body></html>