Ant Colony Optimization

An Invitation for Contribution!

Ant Colony Optimization

 

The book aims to provide practical help for researchers, and industrial specialists who are interested in using the new science and technology to improve their knowledge and experience in the field of optimization.  

Optimization problems are very important in the field of both scientific and industrial. Some real-life examples of these optimization problems are timetable scheduling, nursing time distribution scheduling, train scheduling, capacity planning, vehicle routing problems, group-shop scheduling problem, portfolio optimization, etc. Many optimizations algorithms are developed for this reason. Ant Colony Optimization (ACO) is one of them. ACO is a probabilistic technique for finding optimal paths. In computer science and researches, the ACO algorithm is used for solving different computational problems.   

There are many optimization problems where the ACO can be applied for finding the optimal solution. Some of them are Image processing, Capacitated vehicles routing, Stochastic vehicles routing, Vehicle routing with pick-up and delivery, Connectionless network routing, Data mining, Group-shop scheduling, Distributed information retrieval, Nursing time distribution, Permutation flow shop problem, Frequency assignment problem, Redundancy allocation problem, and Electricity network design.

The Objective of the book is to provide a concise overview of the state of the art of ACO for industrial researchers. They will value a book that helps them position the emerging capabilities of ACO in their businesses and provide an assessment of where and how these new capabilities can help to optimize the end to end operations of their enterprises.

The book aims to provide practical help for researchers, and industrial specialists who are interested in using the new science and technology to improve their knowledge and experience in the field of optimization.

Optimization problems are very important in the field of both scientific and industrial. Some real-life examples of these optimization problems are timetable scheduling, nursing time distribution scheduling, train scheduling, capacity planning, vehicle routing problems, group-shop scheduling problem, portfolio optimization, etc. Many optimizations algorithms are developed for this reason. Ant Colony Optimization (ACO) is one of them. ACO is a probabilistic technique for finding optimal paths. In computer science and researches, the ACO algorithm is used for solving different computational problems.

There are many optimization problems where the ACO can be applied for finding the optimal solution. Some of them are Image processing, Capacitated vehicles routing, Stochastic vehicles routing, Vehicle routing with pick-up and delivery, Connectionless network routing, Data mining, Group-shop scheduling, Distributed information retrieval, Nursing time distribution, Permutation flow shop problem, Frequency assignment problem, Redundancy allocation problem, and Electricity network design.

The Objective of the book is to provide a concise overview of the state of the art of ACO for industrial researchers. They will value a book that helps them position the emerging capabilities of ACO in their businesses and provide an assessment of where and how these new capabilities can help to optimize the end to end operations of their enterprises.

Topics

The following topics illustrate the target subject areas and scope of the project. These keywords are not definitive but can be used as the basis for the chapter content. We accept theoretical and applied scientific papers which can be presented as original research papers and review papers. The required length of the full chapters is 10-20 pages.