Natural Intelligence for Scheduling, Planning and Packing Problems

Bibliographic Details
Corporate Author:	SpringerLink (Online service)
Other Authors:	Chiong, Raymond. (Editor), Dhakal, Sandeep. (Editor)
Format:	eBook
Language:	English
Published:	Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2009.
Edition:	1st ed. 2009.
Series:	Studies in Computational Intelligence, 250
Subjects:	Artificial intelligence. Production management. Information technology. Business-Data processing. Applied mathematics. Engineering mathematics. Operations research. Decision making. Artificial Intelligence. Operations Management. IT in Business. Mathematical and Computational Engineering. Operations Research/Decision Theory.
Online Access:	https://doi.org/10.1007/978-3-642-04039-9

Table of Contents:

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.

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