Ebook: Intelligent Scheduling Systems

Scheduling is a resource allocation problem which exists in virtually every type of organization. Scheduling problems have produced roughly 40 years of research primarily within the OR community. This community has traditionally emphasized mathematical modeling techniques which seek exact solutions to well formulated optimization problems. While this approach produced important results, many contemporary scheduling problems are particularly difficult. Hence, over the last ten years operations researchers interested in scheduling have turned increasingly to more computer intensive and heuristic approaches. At roughly the same time, researchers in AI began to focus their methods on industrial and management science applications. The result of this confluence of fields has been a period of remarkable growth and excitement in scheduling research.
Intelligent Scheduling Systems captures the results of a new wave of research at the forefront of scheduling research, of interest to researchers and practitioners alike. Presented are an array of the latest contemporary tools -- math modeling to tabu search to genetic algorithms -- that can assist in operational scheduling and solve difficult scheduling problems. The book presents the most recent research results from both operations research (OR) and artificial intelligence (AI) focusing their efforts on real scheduling problems.

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Scheduling is a resource allocation problem which exists in virtually every type of organization. Scheduling problems have produced roughly 40 years of research primarily within the OR community. This community has traditionally emphasized mathematical modeling techniques which seek exact solutions to well formulated optimization problems. While this approach produced important results, many contemporary scheduling problems are particularly difficult. Hence, over the last ten years operations researchers interested in scheduling have turned increasingly to more computer intensive and heuristic approaches. At roughly the same time, researchers in AI began to focus their methods on industrial and management science applications. The result of this confluence of fields has been a period of remarkable growth and excitement in scheduling research.
Intelligent Scheduling Systems captures the results of a new wave of research at the forefront of scheduling research, of interest to researchers and practitioners alike. Presented are an array of the latest contemporary tools -- math modeling to tabu search to genetic algorithms -- that can assist in operational scheduling and solve difficult scheduling problems. The book presents the most recent research results from both operations research (OR) and artificial intelligence (AI) focusing their efforts on real scheduling problems.

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Scheduling is a resource allocation problem which exists in virtually every type of organization. Scheduling problems have produced roughly 40 years of research primarily within the OR community. This community has traditionally emphasized mathematical modeling techniques which seek exact solutions to well formulated optimization problems. While this approach produced important results, many contemporary scheduling problems are particularly difficult. Hence, over the last ten years operations researchers interested in scheduling have turned increasingly to more computer intensive and heuristic approaches. At roughly the same time, researchers in AI began to focus their methods on industrial and management science applications. The result of this confluence of fields has been a period of remarkable growth and excitement in scheduling research.
Intelligent Scheduling Systems captures the results of a new wave of research at the forefront of scheduling research, of interest to researchers and practitioners alike. Presented are an array of the latest contemporary tools -- math modeling to tabu search to genetic algorithms -- that can assist in operational scheduling and solve difficult scheduling problems. The book presents the most recent research results from both operations research (OR) and artificial intelligence (AI) focusing their efforts on real scheduling problems.

Content:
Front Matter....Pages i-x
A Survey of Intelligent Scheduling Systems....Pages 1-40
Schedulers & Planners: What and How Can We Learn From Them....Pages 41-62
Decision-Theoretic Control of Constraint-Satisfaction and Scheduling....Pages 63-78
Guided Forward Search in Tardiness Scheduling of Large One Machine Problems....Pages 79-100
An Overview of Tabu Search Approaches to Production Scheduling Problems....Pages 101-127
Measuring the Quality of Manufacturing Schedules....Pages 129-154
Reactive Scheduling Systems....Pages 155-192
Intelligent Scheduling with Machine Learning....Pages 193-214
Solving Large Integer Programs Arising from Air Traffic Flow Problems....Pages 215-226
Intelligent Scheduling Support for the U.S. Coast Guard....Pages 227-247
Back Matter....Pages 249-260

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Scheduling is a resource allocation problem which exists in virtually every type of organization. Scheduling problems have produced roughly 40 years of research primarily within the OR community. This community has traditionally emphasized mathematical modeling techniques which seek exact solutions to well formulated optimization problems. While this approach produced important results, many contemporary scheduling problems are particularly difficult. Hence, over the last ten years operations researchers interested in scheduling have turned increasingly to more computer intensive and heuristic approaches. At roughly the same time, researchers in AI began to focus their methods on industrial and management science applications. The result of this confluence of fields has been a period of remarkable growth and excitement in scheduling research.
Intelligent Scheduling Systems captures the results of a new wave of research at the forefront of scheduling research, of interest to researchers and practitioners alike. Presented are an array of the latest contemporary tools -- math modeling to tabu search to genetic algorithms -- that can assist in operational scheduling and solve difficult scheduling problems. The book presents the most recent research results from both operations research (OR) and artificial intelligence (AI) focusing their efforts on real scheduling problems.

Content:
Front Matter....Pages i-x
A Survey of Intelligent Scheduling Systems....Pages 1-40
Schedulers & Planners: What and How Can We Learn From Them....Pages 41-62
Decision-Theoretic Control of Constraint-Satisfaction and Scheduling....Pages 63-78
Guided Forward Search in Tardiness Scheduling of Large One Machine Problems....Pages 79-100
An Overview of Tabu Search Approaches to Production Scheduling Problems....Pages 101-127
Measuring the Quality of Manufacturing Schedules....Pages 129-154
Reactive Scheduling Systems....Pages 155-192
Intelligent Scheduling with Machine Learning....Pages 193-214
Solving Large Integer Programs Arising from Air Traffic Flow Problems....Pages 215-226
Intelligent Scheduling Support for the U.S. Coast Guard....Pages 227-247
Back Matter....Pages 249-260
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