Integer Optimization by Local Search : A Domain-Independent Approach - H. Kautz

Instant online reading.
Don't wait for delivery!

Integer Optimization by Local Search

A Domain-Independent Approach

By: H. Kautz (Foreword by), Joachim P. Walser

Write A Review

Paperback | 4 August 1999

At a Glance

Paperback
164 Pages

Dimensions(cm)
22.86 x 15.88 x 1.27

Paperback

$84.99

or 4 interest-free payments of $21.25 with

Ships in 5 to 7 business days

Integer Optimization addresses a wide spectrum of practically important optimization problems and represents a major challenge for algorithmics. The goal of integer optimization is to solve a system of constraints and optimization criteria over discrete variables.
Integer Optimization by Local Search introduces a new approach to domain-independent integer optimization, which, unlike traditional strategies, is based on local search. It develops the central concepts and strategies of integer local search and describes possible combinations with classical methods from linear programming. The surprising effectiveness of the approach is demonstrated in a variety of case studies on large-scale, realistic problems, including production planning, timetabling, radar surveillance, and sports scheduling. The monograph is written for practitioners and researchers from artificial intelligence and operations research.

Shipping

	Standard Shipping	Express Shipping
Metro postcodes:	$9.99	$14.95
Regional postcodes:	$9.99	$14.95
Rural postcodes:	$9.99	$14.95

Orders over $79.00 qualify for free shipping.

How to return your order

At Booktopia, we offer hassle-free returns in accordance with our returns policy. If you wish to return an item, please get in touch with Booktopia Customer Care.

Additional postage charges may be applicable.

Defective items

If there is a problem with any of the items received for your order then the Booktopia Customer Care team is ready to assist you.

For more info please visit our Help Centre.

Introduction	p. 1
Integer Optimization and Heuristics	p. 1
Integer Local Search	p. 5
Experimental Results	p. 7
Research Contributions	p. 9
Frameworks for Combinatorial Optimization	p. 11
Integer Programming Branch- and- Bound	p. 11
Finite Domain Constraint Programming	p. 13
Local Search	p. 15
Meta- heuristics	p. 16
RISC and CISC Local Search	p. 17
Local Search for SAT	p. 18
Application Domains of SAT Local Search	p. 20
Modeling Languages	p. 21
Search Relaxations and Integer Local Search	p. 21
Local Search for Integer Constraints	p. 25
Over- Constrained Integer Programs	p. 25
Definition	p. 27
Relation to Integer Linear Programs	p. 28
Constraint-Bounds	p. 31
Integer Local Search: Wsat(oip)	p. 32
The Score	p. 33
The Main Loop	p. 34
Move Selection and Tabu Search Extensions	p. 34
Combinations with Linear Programming	p. 37
Bounds from LP Relaxations	p. 37
Initialization by Rounding LP Solutions	p. 38
Search Space Reduction Using LP Reduced Costs	p. 40
Implementation Issues	p. 41
A Graphical Interpretation	p. 43
Related Work	p. 47
Integer Programming Heuristics	p. 48
Local Search in Constraint Satisfaction	p. 51
Summary	p. 51
Case Studies Methodology	p. 53
Optimization in Practice: Criteria of Success	p. 53
Scaling with Increasing Problem Size	p. 54
Scaling with Increasing Constrainedness	p. 55
Flexibility and Residual Robustness	p. 56
The Problem Class Selection	p. 56
The Empirical Comparisons	p. 57
Time-Tabling and Sports Scheduling	p. 59
The Progressive Party Problem	p. 59
Problem Description and Formulation	p. 60
Experimental Results and Comparison	p. 62
The ACC Basketball Scheduling Problem	p. 64
Double Round Robin Scheduling	p. 65
Problem Specification of ACC97/98	p. 66
Integer Local Search Formulation	p. 68
Redundant Constraints	p. 71
Previous (Multi- stage) Approaches	p. 72
Experimental Results under Varied Constrainedness	p. 73
Minimal Distortion Mirroring	p. 76
Conclusions	p. 78
Covering and Assignment	p. 81
Radar Surveillance Covering	p. 81
Problem Description and Formulation	p. 81
Experimental Results under Varied Problem Size	p. 83
Course Assignment	p. 87
Problem Description and Formulation	p. 87
Experimental Results under Varied Problem Size	p. 89
A Related Application: Reviewer Assignment	p. 91
Conclusions	p. 93
Capacitated Production Planning	p. 95
Capacitated Lot- Sizing	p. 96
Integer Local Search Formulation	p. 98
Mixed Integer Programming Formulation	p. 99
Lagrangean Relaxation Approach	p. 100
Restricting the Problem	p. 101
Experimental Results	p. 101
Comparison of Results	p. 101
Lower Bounds	p. 104
Conclusions	p. 105
Extensions	p. 107
Current Limitations	p. 107
An Alternative Scoring Scheme	p. 108
Future Research	p. 111
Conclusions	p. 112
A Complete AMPL Model for ACC97/98	p. 115
References	p. 122
Index	p. 135
Table of Contents provided by Publisher. All Rights Reserved.

Integer Optimization by Local Search

A Domain-Independent Approach

At a Glance

Paperback

Shipping

How to return your order

Defective items

You Can Find This Book In

More in Optimisation

How to Win At Chess

The Ultimate Guide for Beginners and Beyond

The Infinite Game

From the bestselling author of Start With Why

The Score

How to Stop Playing Someone Else's Game

The Art of Strategy â" A Game Theoristâ²s Guide to Success in Business and Life

A Game Theorist's Guide to Success in Business and Life

The Selfish Gene

40th Anniversary Edition

Statistical Analysis with R For Dummies

For Dummies (Computer/Tech)

Elementary Linear Algebra

8th Edition - International Metric Edition

Math Games with Bad Drawings

75 1/4 Simple, Challenging, Go-Anywhere Games & And Why They Matter

On the Edge

The Art of Risking Everything

Theory of Games and Economic Behavior

Parabolic Problems

60 Years of Mathematical Puzzles in Parabola

Quantum Machine Learning

Theory, Algorithms, and Practical Implementation

Game Theory

A Very Short Introduction

A Course in Behavioral Economics

3rd edition

Decision Analytics: Mathematical Models and Algori thms for Sequential Decisionâ"Making

Mathematical Models and Algorithms for Sequential Decision-Making

When War Is the Answer

The Rational Case for Conflict, and Why Leaders Don't Always Choose Peace

Ciphers, Fractals, and Fibonacci

Exploring Math with Python

Industrial Engineering and Operations Management - I

XXXI IJCIEOM, Bari, Italy, June 23-25, 2025

PDEs, Control and Deep Learning

Cetraro, Italy 2024

A History of Mathematics in Economics

From Aristotle to Artificial Intelligence

Astral Space

Convex Analysis at Infinity

Advanced Intelligence Methods for Data Science and Optimization

Modern Numerical Nonlinear Optimization

Springer Optimization and Its Applications

Game-Theoretic Models of International Crisis Bargaining

Methodological Tools in the Social Sciences

This product is categorised by