Correct predictions are in blue. If we detect only a subset of a labelled sentence, we highlight the caught part as blue, the missing part light blue. False positives are in green and false negatives are in red.

Problem Yield_Management — Constraint detection

An airline is selling tickets for flights to a particular destination . The flight will depart in three weeks ' time . It can use up to six planes each costing pounds 50000 to hire . Each plane has the following : 37 First Class seats , 38 Business Class seats , 47 Economy Class seats . Up to 10 % of seats in any one category can be transferred to an adjacent category . It wishes to decide a price for each of these seats . There will be further opportunities to update these prices after one week and two weeks . Once a customer has purchased a ticket , there is no cancellation option . For administrative simplicity , three price level options are possible in each class -LRB- one of which must be chosen -RRB- . The same option need not be chosen for each class . These are given in a table for the current period -LRB- period 1 -RRB- and two future periods . Demand is uncertain but will be affected by price . Forecasts have been made of these demands according to a probability distribution that divides the demand levels into three scenarios for each period . The probabilities of the three scenarios in each period are as follows : 0.1 -LRB- scenario 1 -RRB- , 0.7 -LRB- scenario 2 -RRB- , 0.2 -LRB- scenario 3 -RRB- . The forecast demands are shown in a table . Decide price levels for the current period , how many seats to sell in each class -LRB- depending on demand -RRB- , the provisional number of planes to book and provisional price levels and seats to sell in future periods in order to maximise expected yield . You should schedule to be able to meet commitments under all possible combinations of scenarios .

Problem Yield_Management — Detection of the decisions and objects to be modeled

An airline is selling tickets for flights to a particular destination . The flight will depart in three weeks ' time . It can use up to six planes each costing pounds 50000 to hire . Each plane has the following : 37 First Class seats , 38 Business Class seats , 47 Economy Class seats . Up to 10 % of seats in any one category can be transferred to an adjacent category . It wishes to decide a price for each of these seats . There will be further opportunities to update these prices after one week and two weeks . Once a customer has purchased a ticket , there is no cancellation option . For administrative simplicity , three price level options are possible in each class -LRB- one of which must be chosen -RRB- . The same option need not be chosen for each class . These are given in a table for the current period -LRB- period 1 -RRB- and two future periods . Demand is uncertain but will be affected by price . Forecasts have been made of these demands according to a probability distribution that divides the demand levels into three scenarios for each period . The probabilities of the three scenarios in each period are as follows : 0.1 -LRB- scenario 1 -RRB- , 0.7 -LRB- scenario 2 -RRB- , 0.2 -LRB- scenario 3 -RRB- . The forecast demands are shown in a table . Decide price levels for the current period , how many seats to sell in each class -LRB- depending on demand -RRB- , the provisional number of planes to book and provisional price levels and seats to sell in future periods in order to maximise expected yield . You should schedule to be able to meet commitments under all possible combinations of scenarios .

Back to list