Metaheuristics for Hard Optimization: Methods and Case Studies


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Methods and Case Studies

The last chapter is devoted to the problem of the choice of a metaheuristic; we describe an unifying method called "Adaptive Memory Programming", which tends to attenuate the difficulty of this choice.

International Journal of Metaheuristics

The delicate subject of a rigorous statistical comparison between stochastic iterative methods is also discussed. The last part of the book concentrates on three case studies: - the optimization of the 3G mobile networks UMTS using the genetic algorithms. After a brief presentation of the operation of UMTS networks and of the quantities involved in the analysis of their performances, the chapter discusses the optimization problem for planning the UMTS network; an efficient method using a genetic algorithm is presented and illustrated through one example of a realistic network; - the application of genetic algorithms to the problems of management of the air traffic.

One details two problems of air traffic management for which a genetic algorithm based solution has been proposed: the first application deals with the en route conflict resolution problem; the second one discusses the traffic management in an airport platform; - constrained programming and ant colony algorithms applied to vehicle routing problems.

It is shown that constraint programming provides a modelling procedure, making it possible to represent the problems in an expressive and concise way; the use of ant colony algorithms allows to obtain heuristics which can be simultaneously robust and generic in nature. One appendix of the book is devoted to the modeling of simulated annealing through the Markov chain formalism.

Keywords : Global optimization Metaheuristics Optimization. Document type : Books. Identifiers HAL Id : hal, version 1.

Morton D. Michael Maschler.

Metaheuristics for Hard Optimization

The Bounds of Reason. Herbert Gintis. Bruce Bueno de Mesquita. Aviad Heifetz. A Gentle Introduction to Optimization. Bertrand Guenin. Joel Watson. Steven Tadelis. Michael Allingham. Your review has been submitted successfully. Not registered? Forgotten password Please enter your email address below and we'll send you a link to reset your password.

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Johann Dreo - Google Scholar Citations

Management Science, 50 1 , — Lodi, A. Informs Journal of Computing, 11 4 , Recent advances on two-dimensional bin packing problems. Discrete Applied Mathematics, 1—3 , — Competing For Shelf Space.

Production and Operations Management, 20 1 , Mavridou, T. Simulated annealing and genetic algorithms for the facility layout problem: A survey. Computational Optimization and Applications, 7, Michael, D. Misevicius, A. An intensive search algorithm for the quadratic assignment problem.


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Informatica, 11, A modification of tabu search and its applications to the quadratic assignment problem. Information Technology and Control, 27, Nissen, V. A modification of threshold accepting and its application to the quadratic assignment problem. OR Spektrum, 17 , Peng, T. Simulated annealing for the quadratic assignment problem: A further study.


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Computers and Industrial Engineering, 31 , Pisinger, D. Algorithms for Knapsack Problems. Applying iterated local search to the permutation flow shop problem. Tian, P. Application of the simulated annealing algorithm to the combinatorial optimization problem with permutation property: An investigation of generation mechanism. European Journal of Operational Research, 1 , Tsuchiya, K. A deterministic annealing algorithm for a combinatorial optimization problem using replicator equations.

Physica D: Nonlinear Phenomena, 3 , Siu, F. Effectiveness of optimal node assignments in wavelength division multiplexing networks with fixed regular virtual topologies. Computer Networks, 38 1 , Thonemann, U. Yang, M.

An effective algorithm to allocate shelf space. A study on shelf space allocation and management. International Journal of Production Economics, ,

Metaheuristics for Hard Optimization: Methods and Case Studies Metaheuristics for Hard Optimization: Methods and Case Studies
Metaheuristics for Hard Optimization: Methods and Case Studies Metaheuristics for Hard Optimization: Methods and Case Studies
Metaheuristics for Hard Optimization: Methods and Case Studies Metaheuristics for Hard Optimization: Methods and Case Studies
Metaheuristics for Hard Optimization: Methods and Case Studies Metaheuristics for Hard Optimization: Methods and Case Studies
Metaheuristics for Hard Optimization: Methods and Case Studies Metaheuristics for Hard Optimization: Methods and Case Studies
Metaheuristics for Hard Optimization: Methods and Case Studies Metaheuristics for Hard Optimization: Methods and Case Studies

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