Hierarchical optimization on an unbounded parallel-batching machine
RAIRO - Operations Research - Recherche Opérationnelle, Tome 52 (2018) no. 1, pp. 55-60.

This paper studies a hierarchical optimization problem on an unbounded parallel-batching machine, in which two objective functions are maximum costs, representing different purposes of two decision-makers. By a hierarchical optimization problem, we mean the problem of optimizing the secondary criterion under the constraint that the primary criterion is optimized. A parallel-batching machine is a machine that can handle several jobs in a batch in which all jobs start and complete respectively at the same time. We present an O(n4)-time algorithm for this hierarchical scheduling problem.

Reçu le :
Accepté le :
DOI : 10.1051/ro/2017089
Classification : 90B35, 90C29
Mots-clés : Hierarchical optimization, batching machine, maximum cost
He, Cheng 1 ; Li, Li 1

1
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He, Cheng; Li, Li. Hierarchical optimization on an unbounded parallel-batching machine. RAIRO - Operations Research - Recherche Opérationnelle, Tome 52 (2018) no. 1, pp. 55-60. doi : 10.1051/ro/2017089. http://archive.numdam.org/articles/10.1051/ro/2017089/

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