Fox, M. S.


Constraint-guided scheduling: A short history of research at CMU

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Mark S. Fox received his BSc in Computer Science from the University of Toronto in 1975 and his PhD in Computer Science from Carnegie Mellon University in 1983. Carnegie Mellon University appointed him Associate Professor of Computer Science and Robotics in 1987. In 1988 he was appointed Director of the new Center for Integrated Manufacturing Decision Systems, which is one of the largest centers in the US for research in intelligent systems to solve engineering and manufacturing problems. Research interests include knowledge representation, constraint directed reasoning and applications of artificial intelligence to engineering and manufacturing problems.


ISIS: A knowledge-based system for factory scheduling

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"Analysis of the job shop scheduling domain has indicated that the crux of the scheduling problem is the determination and satisfaction of a large variety of constraints. Schedules are influenced by such diverse and conflicting factors as due date requirements, cost restrictions, production levels, machine capabilities and substitutability, alternative production processes, order characteristics, resource requirements, and resource availability. This paper describes ISIS, a scheduling system capable of incorporating all relevant constraints in the construction of job shop schedules. We examine both the representation of constraints within ISIS, and the manner in which these constraints are used in conducting a constraint-directed search for an acceptable schedule. The important issues relating to the relaxation of constraints are addressed. Finally, the interactive scheduling facilities provided by ISIS are considered." Expert Systems l(l):25-49


Job shop scheduling: An investigation in constraint-directed reasoning

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Each operation in a process routing requires resources such as machines, tools, operators, fixtures, materials, etc. They include job tardiness, work in process, resource levels, cost, production levels, and shop stability. Restriction: (OR exclusive inclusive) Default: exclusive } }} Figure 3-3: discrete-constraint Schema A discrete-constraint contains an ALTERNATIVE slot which specifies alternative discrete values and their utilities. That is, to define: -the constraints that bound the search space, which in turn define the search operators, -any new constraints that do not already exist, -the constraint classes to be ignored, and -a prioritization of the classes.