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Banach, Fréchet, Hilbert and Neumann Spaces

Analysis for PDEs Set Volume 1

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Semi-Markov Migration Models for Credit Risk

Stochastic Models for Insurance Set Volume 1

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Human Exposure to Electromagnetic Fields

From Extremely Low Frequency (ELF) to Radio Frequency

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Enterprise Interoperability

INTEROP-PGSO Vision

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Data Treatment in Environmental Sciences

Multivaried Approach

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From Pinch Methodology to Pinch-Exergy Integration of Flexible Systems

Thermodynamics Energy, Environment, Economy Set

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Exterior Algebras

Elementary Tribute to Grassmann's Ideas

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Nonlinear Theory of Elastic Plates

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Cognitive Approach to Natural Language Processing

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Graph-related Optimization and Decision Support Systems

FOCUS Series in Computer Engineering

Saoussen Krichen, LARODEC Laboratory and Faculty of Law, Economics and Management, University of Jendouba Jouhaina Chaouachi, IHEC Carthage, Tunisia

ISBN: 9781848217430

Publication Date: August 2014   Hardback   184 pp.

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Description

Constrained optimization is a challenging branch of operations research that aims to create a model which has a wide range of applications in the supply chain, telecommunications and medical fields. As the problem structure is split into two main components, the objective is to accomplish the feasible set framed by the system constraints. The aim of this book is expose optimization problems that can be expressed as graphs, by detailing, for each studied problem, the set of nodes and the set of edges. This graph modeling is an incentive for designing a platform that integrates all optimization components in order to output the best solution regarding the parameters' tuning. The authors propose in their analysis, for optimization problems, to provide their graphical modeling and mathematical formulation and expose some of their variants. As a solution approaches, an optimizer can be the most promising direction for limited-size instances. For large problem instances, approximate algorithms are the most appropriate way for generating high quality solutions. The authors thus propose, for each studied problem, a greedy algorithm as a problem-specific heuristic and a genetic algorithm as a metaheuristic.

Contents

1. Basic Concepts in Optimization and Graph Theory.
2. Knapsack Problems.
3. Packing Problems.
4. Assignment Problem.
5. The Resource Constrained Project Scheduling Problem.
6. Spanning Tree Problems.
7. Steiner Problems.
8. A DSS Design for Optimization Problems.

About the Authors

Saoussen Krichen, LARODEC Laboratory and Faculty of Law, Economics and Management, University of Jendouba, Tunisia.
Jouhaina Chaouachi, IHEC Carthage, Tunisia.

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