-- A naive implementation that is slow for all but the smallest instances
-- (30s on a 20x50 example).
-minCostFlow = NaiveMinCostFlow.minCostFlow,
+--minCostFlow = NaiveMinCostFlow.minCostFlow,
-- Uses CS2 (http://www.igsystems.com/cs2/), which requires a license for
-- non-research use but is faster (<1s on a 20x50 example, 64s on a 60x500
-- example). Configure the path to cs2.exe in CS2MinCostFlow.hs. Remember to
-- compile CS2 with -DPRINT_ANS, or this won't work!
---minCostFlow = CS2MinCostFlow.minCostFlow,
+minCostFlow = CS2MinCostFlow.minCostFlow,
-- The number of reviews each proposal should get.
reviewsEachProposal = 4,
+-- Applies to non-PC papers
+pcReviewsEachProposal = 3,
+
-- === Interpretation of the preference values ===
expIsExpert = \x -> x >= 3,
-- load of (relativeLoad * ceiling(numProps * reviewsEachProposal /
-- totalRelativeLoad)). For now this is an additive constant; perhaps it should
-- be proportional to the target load.
-loadTolerance = 3,
+loadTolerance = 2,
+
+ercLoadTolerance = 3,
-- Cost to overload by one review.
-- tx = 0 at target load, 1 at end of tolerance.
assignmentCost = \pref -> (widenInteger 10 + prefNewToOld pref) ^ 2,
-- Bonus for a first knowledgeable or expert review.
-knowledgeableBonus = 1000,
+knowledgeableBonus = 3000,
-- Bonus for an additional expert review.
-expertBonus = 1000,
+expertBonus = 3000,
-- === Parameters for the random-instance generator ===