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Evolutionary Scheduling

Overview of attention for book
Cover of 'Evolutionary Scheduling'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 Memetic Algorithms in Planning, Scheduling, and Timetabling
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    Chapter 2 Landscapes, Embedded Paths and Evolutionary Scheduling
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    Chapter 3 Scheduling of Flow-Shop, Job-Shop, and Combined Scheduling Problems using MOEAs with Fixed and Variable Length Chromosomes
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    Chapter 4 Designing Dispatching Rules to Minimize Total Tardiness
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    Chapter 5 A Robust Meta-Hyper-Heuristic Approach to Hybrid Flow-Shop Scheduling
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    Chapter 6 Hybrid Particle Swarm Optimizers in the Single Machine Scheduling Problem: An Experimental Study
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    Chapter 7 An Evolutionary Approach for Solving the Multi-Objective Job-Shop Scheduling Problem
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    Chapter 8 Multi-Objective Evolutionary Algorithm for University Class Timetabling Problem
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    Chapter 9 Metaheuristics for University Course Timetabling
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    Chapter 10 Optimum Oil Production Planning using an Evolutionary Approach
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    Chapter 11 A Hybrid Evolutionary Algorithm for Service Restoration in Power Distribution Systems
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    Chapter 12 Evolutionary Scheduling
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    Chapter 13 Evolutionary Generator Maintenance Scheduling in Power Systems
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    Chapter 14 Evolvable Fuzzy Scheduling Scheme for Multiple-ChannelPacket Switching Network
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    Chapter 15 A Multi-Objective Evolutionary Algorithm for Channel Routing Problems
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    Chapter 16 Simultaneous Planning and Scheduling for Multi-Autonomous Vehicles
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    Chapter 17 Scheduling Production and Distribution of Rapidly Perishable Materials with Hybrid GA's
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    Chapter 18 A Scenario-based Evolutionary Scheduling Approach for Assessing Future Supply Chain Fleet Capabilities
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    Chapter 19 Evolutionary Optimization of Business Process Designs
  21. Altmetric Badge
    Chapter 20 Using a Large Set of Low Level Heuristics in a Hyperheuristic Approach to Personnel Scheduling
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    Chapter 21 A Genetic-Algorithm-Based Reconfigurable Scheduler
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    Chapter 22 Evolutionary Algorithm for an Inventory Location Problem
Attention for Chapter 10: Optimum Oil Production Planning using an Evolutionary Approach
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (89th percentile)

Mentioned by

patent
4 patents

Citations

dimensions_citation
24 Dimensions

Readers on

mendeley
12 Mendeley
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Chapter title
Optimum Oil Production Planning using an Evolutionary Approach
Chapter number 10
Book title
Evolutionary Scheduling
Published in
Studies in Computational Intelligence, January 2007
DOI 10.1007/978-3-540-48584-1_10
Book ISBNs
978-3-54-048582-7, 978-3-54-048584-1
Authors

Ray, Tapabrata, Sarker, Ruhul, Tapabrata Ray, Ruhul Sarker

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Norway 1 8%
Unknown 11 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 25%
Student > Master 2 17%
Researcher 2 17%
Professor 1 8%
Lecturer > Senior Lecturer 1 8%
Other 1 8%
Unknown 2 17%
Readers by discipline Count As %
Computer Science 5 42%
Engineering 3 25%
Decision Sciences 1 8%
Mathematics 1 8%
Unknown 2 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 30 April 2014.
All research outputs
#3,922,282
of 25,992,468 outputs
Outputs from Studies in Computational Intelligence
#1
of 1 outputs
Outputs of similar age
#14,293
of 170,691 outputs
Outputs of similar age from Studies in Computational Intelligence
#1
of 1 outputs
Altmetric has tracked 25,992,468 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.0. This one scored the same or higher as 0 of them.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 170,691 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 89% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them