@Book{glover03a,
  editor =	 {Fred Glover and Gary A. Kochenberger},
  title =	 {Handbook of Metaheuristics},
  publisher =	 {Springer},
  year =	 2003,
  abstract =	 {The Handbook of Metaheuristics provides both the
                  research and practitioner communities with a
                  comprehensive coverage of the metaheuristic
                  methodologies that have proven to be successful in a
                  wide variety of real-world problem
                  settings. Moreover, it is these metaheuristic
                  strategies that hold particular promise for success
                  in the future. The various chapters serve as stand
                  alone presentations giving both the necessary
                  background underpinnings as well as practical guides
                  for implementation. In most settings a problem
                  solver has an option as to which metaheuristic
                  approach should be adopted for the problem at
                  hand. Alternative methodologies typically exist that
                  could be employed to produce high quality
                  solutions. Often it becomes a matter of choosing one
                  of several approaches that could be adopted. The
                  very nature of metaheuristics invites an analyst to
                  modify basic methods in response to problem
                  characteristics, past experiences, and personal
                  preferences. The chapters in this handbook are
                  designed to facilitate this as well. This Handbook
                  consists of 19 chapters. Topics covered include
                  Scatter Search, Tabu Search, Genetic Algorithms,
                  Genetic Programming, Memetic Algorithms, Variable
                  Neighborhood Search, Guided Local Search, GRASP, Ant
                  Colony Optimization, Simulated Annealing, Iterated
                  Local Search, Multi-Start Methods, Constraint
                  Programming, Constraint Satisfaction, Neural Network
                  Methods for Optimization, Hyper-Heuristics, Parallel
                  Strategies for Metaheuristics, Metaheuristic Class
                  Libraries, and A-Teams. This family of metaheuristic
                  chapters provides a state-of-the-art, comprehensive
                  coverage of the major topics and methodologies of
                  modern metaheuristics.},
  isbn = 	 {1402072635},
  googleprint =  {O_10T_KeqOgC},
  cluster = 	 {7689323197471116007}
}