University of Oregon

On Time Systems, Inc.

Andrew Parkes

Matthew L Ginsberg

Andrew B Baker

Daniel B Keith

Bryan Smith

Tristan Smith

Increased efficiency and lower cost job scheduling is provided by a system and method that optimizes for cost instead of makespan, and minimizes fluctuations in resource utilization. A schedule is constructed using a workflow scheduling system that includes a load leveler, a cost minimizer, and a manpower planner. The load leveler minimizes makespan, subject to resource limits, and then lowers the resource limits, repeating the process in order to create a flatter schedule. The cost minimizer generates an initial solution, and then incrementally improves it, using the manpower planner to evaluate the different possible solutions. The manpower planner calculates, for a given schedule, the optimal hire/fire decisions to minimize total cost.

System and process for job scheduling to minimize construction costs

Subsearch, where a satisfiability algorithm searches through the original theory for ground clauses that satisfy some numeric property, is represented in terms of S(C,P,u,s), the set of ground instances of C that have u literals unvalued by P and s literals satisfied by the assignments in P. This representation allows an intelligent search to be performed to answer subsearch problems posed in terms of S(C,P,u,s). Intelligent Subsearch uses truth value assignments to atoms to eliminate sets of bindings to universally quantified variables within a quantified clausal constraint; the bindings being eliminated because the bindings cannot satisfy a specific statement. Intelligent subsearch backtracks away from poor choices in the search for bindings to variables within the quantified clauses. In typical uses, intelligent subsearch can reduce the time of the checking problem from O(D ) to O(D ) for some &agr;<1.

Satisfiability algorithms and finite quantification

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Walsall, United Kingdom

Andrew Parkes