Research map / Learning theory and algorithms / Combinatorial and search optimization
Dynamic Control of Probabilistic Simple Temporal Networks
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| use Min-Loss DC instead of SREA (strong controllability) | PSTN dispatch · DREAM benchmark | execution success rate: 0.22 -> 0.46 | Helped |
| use Min-Loss DC instead of DC-Dispatch | PSTN dispatch · DREAM benchmark | execution success rate: 0.32 -> 0.46 | Helped |
| use Min-Loss DC instead of DREA (online re-optimization) | PSTN dispatch · DREAM benchmark | execution success rate: 0.32 -> 0.46 | Helped |
| use Min-Loss DC instead of SREA | PSTN dispatch · CAR-SHARING | execution success rate: 0.52 -> 0.57 | Helped |
| use Min-Loss DC instead of DREA | PSTN dispatch · CAR-SHARING | execution success rate: 0.55 -> 0.57 | No clear effect |
| use Max-Gain DC instead of DC-Dispatch | PSTN dispatch · DREAM benchmark | execution success rate: 0.32 -> 0.37 | Helped |
| use Max-Gain DC instead of SREA | PSTN dispatch · CAR-SHARING | execution success rate: 0.52 -> 0.50 | Hurt |
| use Max-Gain DC instead of Min-Loss DC (symmetric tail trimming) | PSTN dispatch · DREAM benchmark | execution success rate: 0.46 -> 0.37 | Hurt |
| lower risk level alpha to 0.001 in Min-Loss DC | Min-Loss DC · DREAM and CAR-SHARING | execution success rate | Helped |
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