Library of American University of Madaba
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Coello Coello, Carlos A.
Advances in Multi-Objective Nature Inspired Computing [electronic resource] / edited by Carlos A. Coello Coello, Clarisse Dhaenens, Laetitia Jourdan. - online resource. - Studies in Computational Intelligence, 272 1860-949X ; .
Multi-Objective Combinatorial Optimization: Problematic and Context -- Approximating Pareto-Optimal Sets Using Diversity Strategies in Evolutionary Multi-Objective Optimization -- On the Velocity Update in Multi-Objective Particle Swarm Optimizers -- Approaching Dynamic Multi-Objective Optimization Problems by Using Parallel Evolutionary Algorithms -- ParadisEO-MOEO: A Software Framework for Evolutionary Multi-Objective Optimization -- The Multiobjective Traveling Salesman Problem: A Survey and a New Approach -- On the Performance of Local Search for the Biobjective Traveling Salesman Problem -- A Bi-objective Metaheuristic for Disaster Relief Operation Planning.
The purpose of this book is to collect contributions that deal with the use of nature inspired metaheuristics for solving multi-objective combinatorial optimization problems. Such a collection intends to provide an overview of the state-of-the-art developments in this field, with the aim of motivating more researchers in operations research, engineering, and computer science, to do research in this area. As such, this book is expected to become a valuable reference for those wishing to do research on the use of nature inspired metaheuristics for solving multi-objective combinatorial optimization problems.
9783642112188
Engineering.
Artificial intelligence.
Engineering mathematics.
Engineering.
Appl.Mathematics/Computational Methods of Engineering.
Artificial Intelligence (incl. Robotics).
519
Advances in Multi-Objective Nature Inspired Computing [electronic resource] / edited by Carlos A. Coello Coello, Clarisse Dhaenens, Laetitia Jourdan. - online resource. - Studies in Computational Intelligence, 272 1860-949X ; .
Multi-Objective Combinatorial Optimization: Problematic and Context -- Approximating Pareto-Optimal Sets Using Diversity Strategies in Evolutionary Multi-Objective Optimization -- On the Velocity Update in Multi-Objective Particle Swarm Optimizers -- Approaching Dynamic Multi-Objective Optimization Problems by Using Parallel Evolutionary Algorithms -- ParadisEO-MOEO: A Software Framework for Evolutionary Multi-Objective Optimization -- The Multiobjective Traveling Salesman Problem: A Survey and a New Approach -- On the Performance of Local Search for the Biobjective Traveling Salesman Problem -- A Bi-objective Metaheuristic for Disaster Relief Operation Planning.
The purpose of this book is to collect contributions that deal with the use of nature inspired metaheuristics for solving multi-objective combinatorial optimization problems. Such a collection intends to provide an overview of the state-of-the-art developments in this field, with the aim of motivating more researchers in operations research, engineering, and computer science, to do research in this area. As such, this book is expected to become a valuable reference for those wishing to do research on the use of nature inspired metaheuristics for solving multi-objective combinatorial optimization problems.
9783642112188
Engineering.
Artificial intelligence.
Engineering mathematics.
Engineering.
Appl.Mathematics/Computational Methods of Engineering.
Artificial Intelligence (incl. Robotics).
519