Scheduling

Scheduling is the problem of assigning a set of tasks to a set of resources subject to a set of constraints. Examples of scheduling constraints include deadlines (e.g., job i must be completed by time t), resource capacities (e.g., there are only four drills), precedence constraints on the order of tasks (e.g., a piece must be sanded before it is painted), and priorities on tasks (e.g., finish job j as soon as possible while meeting the other deadlines). Examples of scheduling domains include classical job-shop scheduling, manufacturing scheduling, and transportation scheduling.

CIRL

CIRL has used a variety of techniques to solve scheduling problems. Recent work has made use of nonsystematic techniques such as squeaky wheel optimization and schedule packing (also known as doubleback optimization) to solve problems that arise in manufacturing scheduling. Other work has combined systematic and nonsystematic techniques, such as limited discrepancy search (LDS) with schedule packing, and squeaky wheel with Operations Research methods.

Pointers

Squeaky Wheel Optimization.
An article by David Joslin and Dave Clements describing squeaky wheel and how it was applied to scheduling work in a fiber optic cable assembly plant, and to a standard set of graph coloring problems. Appeared in Journal of Artificial Intelligence Research, May 1999. A conference version of this material appeared in Proc. AAAI in 1998. Compressed postscript.
Cyclic Scheduling.
This paper by Denise Draper, Ari Jonsson, Dave Clements, and David Joslin describes a constraint based approach to cyclical scheduling problems. Appeared in Proceedings of the 16th International Joint Conference on Artificial Intelligence (IJCAI-99).
Heuristic Optimization: A Hybrid AI/OR Approach.
This article describes a combined AI and Operations Research (OR) effort on scheduling problems that produces better solutions than did AI or OR techniques on their own. This was joint work between CIRL and George Nemhauser, Markus Puttlitz, and Martin Savelsbergh at Georgia Tech. Presented at the Workshop on Industrial Constraint-Directed Scheduling, held in conjunction with Proc. CP in 1997. Compressed postscript.
An Approach to Resource Constrained Project Scheduling
This paper by James Crawford gives an overview of an approach to Resource Constrained Project Scheduling (RCPS) problems. The approach is based on the combination of schedule packing (referred to as doubleback optimization in this paper) with LDS, and generated the best known solutions to benchmark problems of realistic size and character. It appeared in the 1996 Artificial Intelligence and Manufacturing Research Planning Workshop. Postscript.
Limited Discrepancy Search
Article introducing limited discrepancy search, developed by Will Harvey and Matt Ginsberg. Appeared in Proc. IJCAI in 1995. Compressed postscript.
Experimental Results on the Application of Satisfiability Algorithms to Scheduling Problems
Article by Andrew Baker and James Crawford, reporting the results of running various solvers on a well known suite of scheduling problems. Appeared in Proc. AAAI in 1994. Compressed postscript.

Application program:
Aircraft assembly
Cable manufacturing

Parent areas:
Problem Domains

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