Matheuristics: Hybridizing Metaheuristics and Mathematical Programming

ISBN-13: 9781441913050 / Angielski / Miękka / 2009 / 270 str.

Vittorio Maniezzo; Thomas Sta1/4tzle; Stefan Voa

Opis

Metaheuristics support managers in decision-making with robust tools that provide high-quality solutions to important applications in business, engineering, economics, and science in reasonable time frames, but finding exact solutions in these applications still poses a real challenge. However, because of advances in the fields of mathematical optimization and metaheuristics, major efforts have been made on their interface regarding efficient hybridization. This edited book will provide a survey of the state of the art in this field by providing some invited reviews by well-known specialists as well as refereed papers from the second Matheuristics workshop to be held in Bertinoro, Italy, June 2008. Papers will explore mathematical programming techniques in metaheuristics frameworks, and especially focus on the latest developments in Mixed Integer Programming in solving real-world problems. Topics to be covered will also include dual information and metaheuristics; metaheuristics for stochastic problems; MIP solvers as search components; decompositions and lower/upper bounds in metaheuristics/MIP codes (MH codes); and real-world case histories of successful MH applications.

Spis treści

Metaheuristics: Intelligent Problem Solving.- Just MIP it#x0021;.- MetaBoosting: Enhancing Integer Programming Techniques by Metaheuristics.- Usage of Exact Algorithms to Enhance Stochastic Local Search Algorithms.- Decomposition Techniques as Metaheuristic Frameworks.- Convergence Analysis of Metaheuristics.- MIP-based GRASP and Genetic Algorithm for Balancing Transfer Lines.- (Meta-)Heuristic Separation of Jump Cuts in a Branch#x0026;Cut Approach for the Bounded Diameter Minimum Spanning Tree Problem.- A Good Recipe for Solving MINLPs.- Variable Intensity Local Search.- A Hybrid Tabu Search for the -Peripatetic Vehicle Routing Problem.

Blurb

1. Metaheuristics: Intelligent Problem Solving

Marco Caserta and Stefan Voß

2. Just MIP it!

Matteo Fischetti, Andrea Lodi, and Domenico Salvagnin

3. MetaBoosting: Enhancing Integer Programming Techniques by Metaheuristics

Jakob Puchinger, Günther R. Raidl, and Sandro Pirkwieser

4. Usage of Exact Algorithms to Enhance Stochastic Local Search Algorithms

Irina Dumitrescu and Thomas Stützle

5. Decomposition Techniques as Metaheuristic Frameworks

Marco Boschetti, Vittorio Maniezzo, and Matteo Roffilli

6. Convergence Analysis of Metaheuristics

Walter J. Gutjahr

7. MIP-based GRASP and Genetic Algorithm for Balancing Transfer Lines

Alexandre Dolgui, Anton Eremeev, and Olga Guschinskaya

8. (Meta-)Heuristic Separation of Jump Cuts in a Branch & Cut Approach for the Bounded Diameter Minimum Spanning Tree Problem

Martin Gruber and Günther R. Raidl

9. A Good Recipe for Solving MINLPs

Leo Liberti, Giacomo Nannicini, and Nenad Mladenovic

10. Variable Intensity Local Search

Snežana Mitrovic-Minic and Abraham P. Punnen

11. A Hybrid Tabu Search for the m-Peripatetic Vehicle Routing Problem
    
    Sandra Ulrich Ngueveu, Christian Prins, and Roberto Wolfer Calvo