The main aim of this volume has been to gather together a selection of recent papers providing new ideas and solutions for a wide spectrum of Knowledge-Driven Computing approaches. More precisely, the ultimate goal has been to collect new knowledge representation, processing and computing paradigms which could be useful to practitioners involved in the area of discussion. To this end, contributions covering both theoretical aspects and practical solutions were preferred.
The main aim of this volume has been to gather together a selection of recent papers providing new ideas and solutions for a wide spectrum of Knowl...
Combinatorial optimisation is a ubiquitous discipline whose usefulness spans vast applications domains. The intrinsic complexity of most combinatorial optimisation problems makes classical methods unaffordable in many cases. To acquire practical solutions to these problems requires the use of metaheuristic approaches that trade completeness for pragmatic effectiveness. Such approaches are able to provide optimal or quasi-optimal solutions to a plethora of difficult combinatorial optimisation problems.
The application of metaheuristics to combinatorial optimisation is an active field...
Combinatorial optimisation is a ubiquitous discipline whose usefulness spans vast applications domains. The intrinsic complexity of most combinator...
Metaheuristics have been shown to be e?ective for di?cult combinatorial op- mization problems appearing in a wide variety of industrial, economic, and sci- ti?c domains. Prominent examples of metaheuristics are evolutionary algorithms, tabu search, simulated annealing, scatter search, memetic algorithms, variable neighborhood search, iterated local search, greedy randomized adaptive search procedures, ant colony optimization, and estimation of distribution algorithms. Problems solved successfully include scheduling, timetabling, network design, transportation and distribution, vehicle...
Metaheuristics have been shown to be e?ective for di?cult combinatorial op- mization problems appearing in a wide variety of industrial, economic, and...
Evolutionary Computation (EC) techniques are e?cient, nature-inspired me- ods based on the principles of natural evolution and genetics. Due to their - ciency and simple underlying principles, these methods can be used for a diverse rangeofactivitiesincludingproblemsolving, optimization, machinelearningand pattern recognition. A large and continuously increasing number of researchers and professionals make use of EC techniques in various application domains. This volume presents a careful selection of relevant EC examples combined with a thorough examination of the techniques used in EC. The...
Evolutionary Computation (EC) techniques are e?cient, nature-inspired me- ods based on the principles of natural evolution and genetics. Due to their ...
This cutting edge volume presents recent advances in the area of adaptativeness in metaheuristic optimization. It includes up-to-date reviews of hyperheuristics and self-adaptation in evolutionary algorithms.
This cutting edge volume presents recent advances in the area of adaptativeness in metaheuristic optimization. It includes up-to-date reviews of hyper...
Combinatorial optimisation is a ubiquitous discipline whose usefulness spans vast applications domains. The intrinsic complexity of most combinatorial optimisation problems makes classical methods unaffordable in many cases. To acquire practical solutions to these problems requires the use of metaheuristic approaches that trade completeness for pragmatic effectiveness. Such approaches are able to provide optimal or quasi-optimal solutions to a plethora of difficult combinatorial optimisation problems.
The application of metaheuristics to combinatorial optimisation is an active field...
Combinatorial optimisation is a ubiquitous discipline whose usefulness spans vast applications domains. The intrinsic complexity of most combinator...
Constitutes the refereed proceedings of the International Conference on the Applications of Evolutionary Computation, EvoApplications 2011, that was held in Torino, Italy, colocated with the Evo 2011 events.
Constitutes the refereed proceedings of the International Conference on the Applications of Evolutionary Computation, EvoApplications 2011, that was h...
Memetic Algorithms (MAs) are computational intelligence structures combining multiple and various operators in order to address optimization problems. The combination and interaction amongst operators evolves and promotes the diffusion of the most successful units and generates an algorithmic behavior which can handle complex objective functions and hard fitness landscapes.
"Handbook of Memetic Algorithms" organizes, in a structured way, all the the most important results in the field of MAs since their earliest definition until now. A broad review including various algorithmic...
Memetic Algorithms (MAs) are computational intelligence structures combining multiple and various operators in order to address optimization proble...
