Natural Intelligence for Scheduling, Planning and Packing Problems

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Chiong, Raymond (Επιμελητής έκδοσης), Dhakal, Sandeep (Επιμελητής έκδοσης)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg, 2009.
• Σειρά: Studies in Computational Intelligence, 250
• Θέματα: Computer science.; Production management.; Operations research.; Decision making.; Information technology.; Business > Data processing.; Artificial intelligence.; Applied mathematics.; Engineering mathematics.; Computer Science.; Artificial Intelligence (incl. Robotics).; Operations Management.; IT in Business.; Appl.Mathematics/Computational Methods of Engineering.; Operation Research/Decision Theory.

Scheduling, planning and packing are ubiquitous problems that can be found in a wide range of real-world settings. These problems transpire in a large variety of forms, and have enormous socio-economic impact. For many years, significant work has been devoted to automating the processes of schedulin...

Πίνακας περιεχομένων:

• Global Optimization in Supply Chain Operations
• Solving Real-World Vehicle Routing Problems with Evolutionary Algorithms
• A Genetic Algorithm with Priority Rules for Solving Job-Shop Scheduling Problems
• An Estimation of Distribution Algorithm for Flowshop Scheduling with Limited Buffers
• Solving Hierarchically Decomposable Problems with the Evolutionary Transition Algorithm
• Electrical Load Forecasting Using a Neural-Fuzzy Approach
• Quantised Problem Spaces and the Particle Swarm Algorithm
• A Coevolutionary Particle Swarm Algorithm for Bi-Level Variational Inequalities: Applications to Competition in Highway Transportation Networks
• Ant Colony Optimization and Its Application to the Vehicle Routing Problem with Pickups and Deliveries
• Evolutionary and Ant Colony Optimization Based Approaches for a Two-Dimensional Strip Packing Problem
• Diagnosis, Configuration, Planning, and Pathfinding: Experiments in Nature-Inspired Optimization
• A Hybrid Intelligent System for Distributed Dynamic Scheduling.