Evolutionary Scheduling

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Keshav Dahal, Kay Chen Tan, Peter I. Cowling
Springer Science & Business Media, Feb 15, 2007 - Computers - 628 pages
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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.

 

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Contents

Memetic Algorithms in Planning Scheduling and Timetabling
1
Landscapes Embedded Paths and Evolutionary Scheduling
31
Scheduling of FlowShop JobShop and Combined Scheduling Problems using MOEAs with Fixed and Variable Length Chromosomes
49
Designing Dispatching Rules to Minimize Total Tardiness
100
A Robust MetaHyperHeuristic Approach to Hybrid FlowShop Scheduling
125
An Experimental Study
143
An Evolutionary Approach for Solving the MultiObjective JobShop Scheduling Problem
165
MultiObjective Evolutionary Algorithm for University Class Timetabling Problem
197
Evolutionary Generator Maintenance Scheduling in Power Systems
349
Evolvable Fuzzy Scheduling Scheme for MultipleChannel Packet Switching Network
383
A MultiObjective Evolutionary Algorithm for Channel Routing Problems
404
Simultaneous Planning and Scheduling for MultiAutonomous Vehicles
437
Scheduling Production and Distribution of Rapidly Perishable Materials with Hybrid GAs
465
A Scenariobased Evolutionary Scheduling Approach for Assessing Future Supply Chain Fleet Capabilities
485
Evolutionary Optimization of Business Process Designs
512
Using a Large Set of Low Level Heuristics in a Hyperheuristic Approach to Personnel Scheduling
543

Metaheuristics for University Course Timetabling
237
Optimum Oil Production Planning using an Evolutionary Approach
273
A Hybrid Evolutionary Algorithm for Service Restoration in Power Distribution Systems
293
Unit Commitment and Economic Dispatch
312
A GeneticAlgorithmBased Reconfigurable Scheduler
577
Evolutionary Algorithm for an Inventory Location Problem
612
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