Ebook: Metaheuristics: Computer Decision-Making

Combinatorial optimization is the process of finding the best, or optimal, so­ lution for problems with a discrete set of feasible solutions. Applications arise in numerous settings involving operations management and logistics, such as routing, scheduling, packing, inventory and production management, lo­ cation, logic, and assignment of resources. The economic impact of combi­ natorial optimization is profound, affecting sectors as diverse as transporta­ tion (airlines, trucking, rail, and shipping), forestry, manufacturing, logistics, aerospace, energy (electrical power, petroleum, and natural gas), telecommu­ nications, biotechnology, financial services, and agriculture. While much progress has been made in finding exact (provably optimal) so­ lutions to some combinatorial optimization problems, using techniques such as dynamic programming, cutting planes, and branch and cut methods, many hard combinatorial problems are still not solved exactly and require good heuristic methods. Moreover, reaching "optimal solutions" is in many cases meaningless, as in practice we are often dealing with models that are rough simplifications of reality. The aim of heuristic methods for combinatorial op­ timization is to quickly produce good-quality solutions, without necessarily providing any guarantee of solution quality. Metaheuristics are high level procedures that coordinate simple heuristics, such as local search, to find solu­ tions that are of better quality than those found by the simple heuristics alone: Modem metaheuristics include simulated annealing, genetic algorithms, tabu search, GRASP, scatter search, ant colony optimization, variable neighborhood search, and their hybrids.

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This book provides state-of-the-art material in decision-making metaheuristics, from both an algorithm and application point of view.
Audience: This book is suitable for professionals and students in computer science, operations research and business, who use quantitative decision-making tools.

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This book provides state-of-the-art material in decision-making metaheuristics, from both an algorithm and application point of view.
Audience: This book is suitable for professionals and students in computer science, operations research and business, who use quantitative decision-making tools.
Content:
Front Matter....Pages i-xv
A Path Relinking Algorithm for the Generalized Assignment Problem....Pages 1-17
The PROBE Metaheuristic and Its Application to the Multiconstraint Knapsack Problem....Pages 19-36
Lagrangian Heuristics for the Linear Ordering Problem....Pages 37-63
Enhancing the Performance of Memetic Algorithms by Using a Matching-Based Recombination Algorithm....Pages 65-90
Multi-Cast Ant Colony System for the Bus Routing Problem....Pages 91-125
Study of Genetic Algorithms with Crossover Based on Confidence Intervals as an Alternative to Classical Least Squares Estimation Methods for Nonlinear Models....Pages 127-151
Variable Neighborhood Search for Nurse Rostering Problems....Pages 153-172
A Potts Neural Network Heuristic for the Class/Teacher Timetabling Problem....Pages 173-186
Genetic Algorithms for the Single Source Capacitated Location Problem....Pages 187-216
An Elitist Genetic Algorithm for Multiobjective Optimization....Pages 217-236
HSF: The iOpt’s Framework to Easily Design Metaheuristic Methods....Pages 237-256
A Distance-Based Selection of Parents in Genetic Algorithms....Pages 257-278
Experimental Pool Design: Input, Output and Combination Strategies for Scatter Search....Pages 279-300
Evolutionary Proxy Tuning for Expensive Evaluation Functions: A Real-Case Application to Petroleum Reservoir Optimization....Pages 301-324
An Analysis of Solution Properties of the Graph Coloring Problem....Pages 325-345
Developing Classification Techniques from Biological Databases Using Simulated Annealing....Pages 347-367
A New Look at Solving Minimax Problems with Coevolutionary Genetic Algorithms....Pages 369-384
A Performance Analysis of Tabu Search for Discrete-Continuous Scheduling Problems....Pages 385-404
Elements for the Description of Fitness Landscapes Associated with Local Operators for Layered Drawings of Directed Graphs....Pages 405-420
Training Multi Layer Perceptron Network Using a Genetic Algorithm as a Global Optimizer....Pages 421-448
Metaheuristics Applied to Power Systems....Pages 449-464
On the Behavior of ACO Algorithms: Studies on Simple Problems....Pages 465-480
Variable Neighborhood Search for the K-Cardinality Tree....Pages 481-500
Heuristics for Large Strip Packing Problems with Guillotine Patterns: An Empirical Study....Pages 501-522
Choosing Search Heuristics by Non-Stationary Reinforcement Learning....Pages 523-544
GRASP for Linear Integer Programming....Pages 545-573
Random Start Local Search and Tabu Search for a Discrete Lot-Sizing and Scheduling Problem....Pages 575-600
New Benchmark Instances for The Steiner Problem in Graphs....Pages 601-614
A Memetic Algorithm for Communication Network Design Taking into Consideration an Existing Network....Pages 615-626
A GRASP Heuristic for the Capacitated Minimum Spanning Tree Problem Using a Memory-Based Local Search Strategy....Pages 627-657
A GRASP-Tabu Search Algorithm for Solving School Timetabling Problems....Pages 659-672
A Local Search Approach for the Pattern Restricted One Dimensional Cutting Stock Problem....Pages 673-698
An Ant System Algorithm for the Mixed Vehicle Routing Problem with Backhauls....Pages 699-719

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This book provides state-of-the-art material in decision-making metaheuristics, from both an algorithm and application point of view.
Audience: This book is suitable for professionals and students in computer science, operations research and business, who use quantitative decision-making tools.
Content:
Front Matter....Pages i-xv
A Path Relinking Algorithm for the Generalized Assignment Problem....Pages 1-17
The PROBE Metaheuristic and Its Application to the Multiconstraint Knapsack Problem....Pages 19-36
Lagrangian Heuristics for the Linear Ordering Problem....Pages 37-63
Enhancing the Performance of Memetic Algorithms by Using a Matching-Based Recombination Algorithm....Pages 65-90
Multi-Cast Ant Colony System for the Bus Routing Problem....Pages 91-125
Study of Genetic Algorithms with Crossover Based on Confidence Intervals as an Alternative to Classical Least Squares Estimation Methods for Nonlinear Models....Pages 127-151
Variable Neighborhood Search for Nurse Rostering Problems....Pages 153-172
A Potts Neural Network Heuristic for the Class/Teacher Timetabling Problem....Pages 173-186
Genetic Algorithms for the Single Source Capacitated Location Problem....Pages 187-216
An Elitist Genetic Algorithm for Multiobjective Optimization....Pages 217-236
HSF: The iOpt’s Framework to Easily Design Metaheuristic Methods....Pages 237-256
A Distance-Based Selection of Parents in Genetic Algorithms....Pages 257-278
Experimental Pool Design: Input, Output and Combination Strategies for Scatter Search....Pages 279-300
Evolutionary Proxy Tuning for Expensive Evaluation Functions: A Real-Case Application to Petroleum Reservoir Optimization....Pages 301-324
An Analysis of Solution Properties of the Graph Coloring Problem....Pages 325-345
Developing Classification Techniques from Biological Databases Using Simulated Annealing....Pages 347-367
A New Look at Solving Minimax Problems with Coevolutionary Genetic Algorithms....Pages 369-384
A Performance Analysis of Tabu Search for Discrete-Continuous Scheduling Problems....Pages 385-404
Elements for the Description of Fitness Landscapes Associated with Local Operators for Layered Drawings of Directed Graphs....Pages 405-420
Training Multi Layer Perceptron Network Using a Genetic Algorithm as a Global Optimizer....Pages 421-448
Metaheuristics Applied to Power Systems....Pages 449-464
On the Behavior of ACO Algorithms: Studies on Simple Problems....Pages 465-480
Variable Neighborhood Search for the K-Cardinality Tree....Pages 481-500
Heuristics for Large Strip Packing Problems with Guillotine Patterns: An Empirical Study....Pages 501-522
Choosing Search Heuristics by Non-Stationary Reinforcement Learning....Pages 523-544
GRASP for Linear Integer Programming....Pages 545-573
Random Start Local Search and Tabu Search for a Discrete Lot-Sizing and Scheduling Problem....Pages 575-600
New Benchmark Instances for The Steiner Problem in Graphs....Pages 601-614
A Memetic Algorithm for Communication Network Design Taking into Consideration an Existing Network....Pages 615-626
A GRASP Heuristic for the Capacitated Minimum Spanning Tree Problem Using a Memory-Based Local Search Strategy....Pages 627-657
A GRASP-Tabu Search Algorithm for Solving School Timetabling Problems....Pages 659-672
A Local Search Approach for the Pattern Restricted One Dimensional Cutting Stock Problem....Pages 673-698
An Ant System Algorithm for the Mixed Vehicle Routing Problem with Backhauls....Pages 699-719
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