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.

This volume chronicles the 16th Annual Conference on System Engineering Research (CSER) held on May 8-9, 2018 at the University of Virginia, Charlottesville, Virginia, USA. The CSER offers researchers in academia, industry, and government a common forum to present, discuss, and influence systems engineering research. It provides access to forward-looking research from across the globe, by renowned academicians as well as perspectives from senior industry and government representatives. Co-founded by the University of Southern California and Stevens Institute of Technology in 2003, CSER has become the preeminent event for researchers in systems engineering across the globe. Topics include though are not limited to the following: Systems in context: * Formative methods: requirements * Integration, deployment, assurance * Human Factors * Safety and Security Decisions/ Control & Design; Systems Modeling: * Optimization, Multiple Objectives, Synthesis * Risk and resiliency * Collaborative autonomy * Coordination and distributed decision-making Prediction: * Prescriptive modeling; state estimation * Stochastic approximation, stochastic optimization and control Integrative Data engineering: * Sensor Management * Design of Experiments

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.