Conference Paper

Minimal Perturbance in Dynamic Scheduling.

Source: DBLP


This paper describes an algorithm, unimodular probing, conceived to optimally reconfigure schedules in response to a changing environ- ment. In the problems studied, resources may become unavailable, and scheduled activities may change. The total shift in the start and end times of activities should be kept to a minimum. This require- ment is captured in terms of a linear optimization function over lin- ear constraints. However, the disjunctive nature of many scheduling problems impedes traditional mathematical programming approaches. The unimodular probing algorithm interleaves constraint program- ming and linear programming. The linear programming solver is ap- plied to a dynamically controlled subset of the problem constraints, to guarantee that the values returned are discrete. Using a r epair strat- egy, these values are naturally integrated into the constra int program- ming search. We explore why the algorithm is effective and discuss its applicability to a wider class of problems. It appears th at other problems comprising disjunctive constraints and a linear o ptimiza- tion function may be suited to the algorithm. Unimodular probing outperforms alternative algorithms on randomly generated bench- marks, and on a major airline application.

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