Evolutionary Scheduling
Series: Studies in Computational Intelligence; 49;
- Publisher's listprice EUR 160.49
-
68 079 Ft (64 837 Ft + 5% VAT)
The price is estimated because at the time of ordering we do not know what conversion rates will apply to HUF / product currency when the book arrives. In case HUF is weaker, the price increases slightly, in case HUF is stronger, the price goes lower slightly.
- Discount 20% (cc. 13 616 Ft off)
- Discounted price 54 463 Ft (51 870 Ft + 5% VAT)
68 079 Ft
Availability
Estimated delivery time: In stock at the publisher, but not at Prospero's office. Delivery time approx. 3-5 weeks.
Not in stock at Prospero.
Why don't you give exact delivery time?
Delivery time is estimated on our previous experiences. We give estimations only, because we order from outside Hungary, and the delivery time mainly depends on how quickly the publisher supplies the book. Faster or slower deliveries both happen, but we do our best to supply as quickly as possible.
Product details:
- Edition number Softcover reprint of hardcover 1st ed. 2007
- Publisher Springer
- Date of Publication 30 November 2010
- Number of Volumes 1 pieces, Previously published in hardcover
- ISBN 9783642080173
- Binding Paperback
- No. of pages628 pages
- Size 235x155 mm
- Weight 967 g
- Language English
- Illustrations XI, 628 p. Tables, black & white 0
Categories
Short description:
Evolutionary scheduling is a vital research domain at the interface of two important sciences - artificial intelligence and operational research. Scheduling problems are generally complex, large scale, constrained, and multi-objective in nature, and classical operational research techniques are often inadequate at solving them effectively. With the advent of computation intelligence, there is renewed interest in solving scheduling problems using evolutionary computational techniques. These techniques, which include genetic algorithms, genetic programming, evolutionary strategies, memetic algorithms, particle swarm optimization, ant colony systems, etc, are derived from biologically inspired concepts and are well-suited to solve scheduling problems since they are highly scalable and flexible in terms of handling constraints and multiple objectives. This edited book gives an overview of many of the current developments in the large and growing field of evolutionary scheduling, and demonstrates the applicability of evolutionary computational techniques to solve scheduling problems, not only to small-scale test problems, but also fully-fledged real-world problems. The intended readers of this book are engineers, researchers, practitioners, senior undergraduates, and graduate students who are interested in the field of evolutionary scheduling.
MoreLong description:
Evolutionary scheduling is a vital research domain at the interface of two important sciences - artificial intelligence and operational research. Scheduling problems are generally complex, large scale, constrained, and multi-objective in nature, and classical operational research techniques are often inadequate at solving them effectively. With the advent of computation intelligence, there is renewed interest in solving scheduling problems using evolutionary computational techniques. These techniques, which include genetic algorithms, genetic programming, evolutionary strategies, memetic algorithms, particle swarm optimization, ant colony systems, etc, are derived from biologically inspired concepts and are well-suited to solve scheduling problems since they are highly scalable and flexible in terms of handling constraints and multiple objectives. This edited book gives an overview of many of the current developments in the large and growing field of evolutionary scheduling, and demonstrates the applicability of evolutionary computational techniques to solve scheduling problems, not only to small-scale test problems, but also fully-fledged real-world problems. The intended readers of this book are engineers, researchers, practitioners, senior undergraduates, and graduate students who are interested in the field of evolutionary scheduling.
MoreTable of Contents:
Methodology.- Memetic Algorithms in Planning, Scheduling, and Timetabling.- Landscapes, Embedded Paths and Evolutionary Scheduling.- Classical and Non-Classical Models of Production Scheduling.- Scheduling of Flow-Shop, Job-Shop, and Combined Scheduling Problems using MOEAs with Fixed and Variable Length Chromosomes.- Designing Dispatching Rules to Minimize Total Tardiness.- A Robust Meta-Hyper-Heuristic Approach to Hybrid Flow-Shop Scheduling.- Hybrid Particle Swarm Optimizers in the Single Machine Scheduling Problem: An Experimental Study.- An Evolutionary Approach for Solving the Multi-Objective Job-Shop Scheduling Problem.- Timetabling.- Multi-Objective Evolutionary Algorithm for University Class Timetabling Problem.- Metaheuristics for University Course Timetabling.- Energy Applications.- Optimum Oil Production Planning using an Evolutionary Approach.- A Hybrid Evolutionary Algorithm for Service Restoration in Power Distribution Systems.- Particle Swarm Optimisation for Operational Planning: Unit Commitment and Economic Dispatch.- Evolutionary Generator Maintenance Scheduling in Power Systems.- Networks.- Evolvable Fuzzy Scheduling Scheme for Multiple-ChannelPacket Switching Network.- A Multi-Objective Evolutionary Algorithm for Channel Routing Problems.- Transport.- Simultaneous Planning and Scheduling for Multi-Autonomous Vehicles.- Scheduling Production and Distribution of Rapidly Perishable Materials with Hybrid GA's.- A Scenario-based Evolutionary Scheduling Approach for Assessing Future Supply Chain Fleet Capabilities.- Business.- Evolutionary Optimization of Business Process Designs.- Using a Large Set of Low Level Heuristics in a Hyperheuristic Approach to Personnel Scheduling.- A Genetic-Algorithm-Based Reconfigurable Scheduler.- Evolutionary Algorithm foran Inventory Location Problem.
More
Evolutionary Scheduling
Subcribe now and receive a favourable price.
Subscribe
68 079 HUF
