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VERSION:2.0
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UID:12cb69b5-c017-4fe1-9452-aed047254234@nexttoyou
DTSTAMP:20261106T174501Z
DTSTART:20261112T203000Z
DTEND:20261112T213000Z
SUMMARY:Neng Fan\, "Agricultural Decision-Making under Drought: Models\, A
 lgorithms\, and Applications"
LOCATION:Benedum Hall 102\, 3700 O'Hara Street\, Pittsburgh\, PA 15261
DESCRIPTION:Abstract:\nAgricultural operations management (AOM) under drou
 ght presents a rich class of multiscale and temporally coupled decision p
 roblems\, spanning activities from individual fields to early-stage logis
 tics. These problems include long-term planting and crop-rotation plannin
 g\, land-use optimization\, irrigation and seasonal water allocation\, ha
 rvesting planning and scheduling\, and the coordination of equipment\, ma
 chinery\, and labor. Beyond upstream production\, AOM also interfaces wit
 h biomass logistics and supply-chain design. In the United States\, much 
 of the West\, particularly the Southwest\, consists of arid and semi-arid
  regions with limited and highly variable annual precipitation. Despite t
 hese climatic constraints\, the Southwestern U.S. is an important produce
 r of high-value specialty crops\, making effective agricultural operation
 s and resource management economically and strategically important.\n\nTh
 is talk presents optimization models\, computational algorithms\, and dec
 ision insights for AOM in the Southwestern U.S. across strategic\, tactic
 al\, and operational timescales. It draws on three streams of recent rese
 arch: planting and crop-rotation planning\, harvesting and machinery sche
 duling\, and biomass supply-chain design for low-water-use\, drought-tole
 rant\, and heat-resistant crops. The models incorporate uncertainties ass
 ociated with crop adoption\, drought scenarios\, water availability\, and
  weather variability. Stochastic optimization models and algorithms addre
 ss th\n\nhttp://next-to-u.app/events/12cb69b5-c017-4fe1-9452-aed047254234
URL:http://next-to-u.app/events/12cb69b5-c017-4fe1-9452-aed047254234
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