We study the problem of scheduling jobs on a serial batching machine to minimize total tardiness. Jobs of the same batch start and are completed simultaneously and the length of a batch equals the sum of the processing times of its jobs. When a new batch starts, a constant setup time occurs. This problem s-batch is known to be NP-Hard in the ordinary sense. In this paper we show that it is solvable in pseudopolynomial time by dynamic programming.
We study the problem of scheduling jobs on a serial batching machine
to minimize total tardiness. Jobs of the same batch start and are
completed simultaneously and the length of a batch equals the sum of
the processing times of its jobs. When a new batch starts, a constant
setup time occurs. This problem
| ∑ is
known to be NP-Hard in the ordinary sense. In this paper we show that
it is solvable in pseudopolynomial time by dynamic programming.
We consider the Airspace Sectorization Problem (ASP) in which airspace has to be partitioned into a given number of sectors, each of which being assigned to a team of air traffic controllers. The objective is to minimize the coordination workload between adjacent sectors while balancing the total workload of controllers. Many specific constraints, including both geometrical and aircraft related constraints are taken into account. The problem is solved in a constraint programming framework. Experimental...
We consider the Airspace Sectorization Problem (ASP) in which airspace
has to be partitioned into a given number of sectors, each of which
being assigned to a team of air traffic controllers. The objective is
to minimize the coordination workload between adjacent sectors while
balancing the total workload of controllers. Many specific
constraints, including both geometrical and aircraft related
constraints are taken into account. The problem is solved in a
constraint programming framework. Experimental...
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