multi objective optimization based ant di masoud rizk (8 risultati)

Condizione: New. pp. 176.

Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Masoud Rizk Allah RizkRizk M. Rizk Allah obtained his Ph.D in Engineering Mathematics from Faculty of Engineering ,Menoufia University, Egypt. He has been with the Basic Engineering Sciences Department, Faculty of Engineering ,Menouf.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Ant Colony Optimization (ACO) is a meta-heuristic algorithm which has been successfully applied to tackle various combinatorial optimization problems, but its ability to cope with multi-objective optimization problems is yet to be explored widely. Since most real-world search and optimization problems are naturally posed as non-linear programming problems having multi-objective problems. Therefore, the principal goal of this work aims to implement a specialized version of the ant colony optimization algorithm capable of finding a set of solutions for multi-objective optimization problems. Features relevant to ant colony optimization include a highly efficient form of best-path exploitation (pheromone detection), and a sensible mechanism for exploration (probabilistic path selection). The results demonstrate superiority of the proposed algorithm and confirm its potential to solve the multi-objective problems and engineering applications. 176 pp. Englisch.

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book introduced a hybrid optimization algorithm that integrates the merits of the ant colony optimization (ACO) and firefly algorithm (FA) that used to solve optimization problems. The methodology of the book is mainly focused on the original principle behind each of the two algorithms and their applications are discussed. Also we introduced new trend for hybridizing the ant colony optimization and the firefly algorithm to solve unconstrained optimization problems, constrained optimization problems and multi-objective optimization problems.

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Ant Colony Optimization (ACO) is a meta-heuristic algorithm which has been successfully applied to tackle various combinatorial optimization problems, but its ability to cope with multi-objective optimization problems is yet to be explored widely. Since most real-world search and optimization problems are naturally posed as non-linear programming problems having multi-objective problems. Therefore, the principal goal of this work aims to implement a specialized version of the ant colony optimization algorithm capable of finding a set of solutions for multi-objective optimization problems. Features relevant to ant colony optimization include a highly efficient form of best-path exploitation (pheromone detection), and a sensible mechanism for exploration (probabilistic path selection). The results demonstrate superiority of the proposed algorithm and confirm its potential to solve the multi-objective problems and engineering applications.

Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Ant Colony Optimization (ACO) is a meta-heuristic algorithm which has been successfully applied to tackle various combinatorial optimization problems, but its ability to cope with multi-objective optimization problems is yet to be explored widely. Since most real-world search and optimization problems are naturally posed as non-linear programming problems having multi-objective problems. Therefore, the principal goal of this work aims to implement a specialized version of the ant colony optimization algorithm capable of finding a set of solutions for multi-objective optimization problems. Features relevant to ant colony optimization include a highly efficient form of best-path exploitation (pheromone detection), and a sensible mechanism for exploration (probabilistic path selection). The results demonstrate superiority of the proposed algorithm and confirm its potential to solve the multi-objective problems and engineering applications.Books on Demand GmbH, Überseering 33, 22297 Hamburg 176 pp. Englisch.

Condizione: New. Print on Demand pp. 176 2:B&W 6 x 9 in or 229 x 152 mm Perfect Bound on Creme w/Gloss Lam.

Condizione: New. PRINT ON DEMAND pp. 176.