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Download PDF by Chandra Sekhar Pedamallu, Linet Özdamar (auth.), Patrick: Advances in Metaheuristics for Hard Optimization

By Chandra Sekhar Pedamallu, Linet Özdamar (auth.), Patrick Siarry, Zbigniew Michalewicz (eds.)

ISBN-10: 3540729593

ISBN-13: 9783540729594

ISBN-10: 3540729607

ISBN-13: 9783540729600

Many advances were made lately in metaheuristic tools, from conception to functions. The editors, either best specialists during this box, have assembled a staff of researchers to give a contribution 21 chapters equipped into elements on simulated annealing, tabu seek, ant colony algorithms, general-purpose experiences of evolutionary algorithms, purposes of evolutionary algorithms, and numerous metaheuristics.

The publication gathers contributions on the topic of the next subject matters: theoretical advancements in metaheuristics; version of discrete metaheuristics to non-stop optimization; functionality comparisons of metaheuristics; cooperative equipment combining diversified techniques; parallel and dispensed metaheuristics for multiobjective optimization; software program implementations; and real-world applications.

This publication is acceptable for practitioners, researchers and graduate scholars in disciplines corresponding to optimization, heuristics, operations learn, and traditional computing.

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Ratschek H, Rokne J () New Computer Methods for Global Optimization. Ellis Horwood, Chichester . Sahinidis N V () Global Optimization and Constraint Satisfaction: The Branchand-Reduce Approach. In: Bliek C, Jermann C, Neumaier A (eds) COCOS , LNCS. Springer, Boston Dordrecht London . Schoenauer M, Michalewicz Z () Evolutionary Computation :– . Smith E M B, Pantelides C. C () Computers and Chemical Engineering :– . Swaney R E () Global Solution of algebraic nonlinear programs.

Swaney R E () Global Solution of algebraic nonlinear programs. AIChE Annual Meeting, Chicago, IL . Visweswaran V, Floudas C A () Computers and Chemical Engineering :– . Wah B W, Wang T () International Journal on Artificial Intelligence Tools :– . Wah B W, Chen Y X () Optimal anytime constrained simulated annealing for constrained global optimization. ) LNCS . Springer, Berlin Heidelberg New York . Wolfe M A () Journal of Computational and Applied Mathematics :– .

To deal with these difficulties, different metaheuristic approaches have been developed. Evolutionary algorithms have been widely applied to multiobjective optimization problems. Here, we present an approach based on tabu search and scatter search as a hybrid method to deal with complex multiobjective optimization problems. This approach is a new version of our multiobjective scatter search (MOSS) [], where new techniques are introduced in order to improve it, and to deal with constrained problems.

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Advances in Metaheuristics for Hard Optimization by Chandra Sekhar Pedamallu, Linet Özdamar (auth.), Patrick Siarry, Zbigniew Michalewicz (eds.)


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