Grouping Genetic Algorithms Advances and Applications /

• Main Authors: Mutingi, Michael (Author), Mbohwa, Charles (Author)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: Cham : Springer International Publishing : Imprint: Springer, 2017.
• Series: Studies in Computational Intelligence, 666
• Subjects: Engineering.; Operations research.; Decision making.; Artificial intelligence.; Management science.; Computational intelligence.; Industrial engineering.; Production engineering.; Computational Intelligence.; Operation Research/Decision Theory.; Artificial Intelligence (incl. Robotics).; Industrial and Production Engineering.; Operations Research, Management Science.

This book presents advances and innovations in grouping genetic algorithms, enriched with new and unique heuristic optimization techniques. These algorithms are specially designed for solving industrial grouping problems where system entities are to be partitioned or clustered into efficient groups...

Table of Contents:

• Part I: Introduction
• Exploring Grouping Problems in Industry
• Complicating Features in Grouping Problems
• Part II: Grouping Genetic Algorithms
• Crouping Genetic Algorithms
• Fuzzy Grouping Genetic Algorithms
• Research Applications
• Fleet Size and Mix Vehicle Routing
• Heterogeneous Vehicle Routing
• Bin Packing: Container-Loading Problems with Compartments
• Homecare Staff Scheduling
• Task Assignment in Home Healthcare Services
• Nursing-Care Task Assignment
• Cell-Manufacturing Systems Design
• Cutting Stock Problem
• Assembly-Line Balancing
• Job-Shop Scheduling
• Equal Piles Problem
• Advertisement Allocation
• Part IV: Conclusions
• Concluding Remarks
• Further Research Considerations.