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The generalized assignment problem with minimum quantities
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DOI：10.1016/j.ejor.2013.01.027.png)
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Abstract
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We consider a variant of the generalized assignment problem (GAP) where the amount of space used in each bin is restricted to be either zero (if the bin is not opened) or above a given lower bound (a minimum quantity). We provide several complexity results for different versions of the problem and give polynomial time exact algorithms and approximation algorithms for restricted cases. For the most general version of the problem, we show that it does not admit a polynomial time approximation algorithm (unless P = NP), even for the case of a single bin. This motivates to study dual approximation algorithms that compute solutions violating the bin capacities and minimum quantities by a constant factor. When the number of bins is fixed and the minimum quantity of each bin is at least a factor delta > 1 larger than the largest size of an item in the bin, we show how to obtain a polynomial time dual approximation algorithm that computes a solution violating the minimum quantities and bin capacities by at most a factor 1 - 1/delta and 1 +1/delta, respectively, and whose profit is at least as large as the profit of the best solution that satisfies the minimum quantities and bin capacities strictly. In particular, for delta = 2, we obtain a polynomial time (1,2)-approximation algorithm. (C) 2013 Elsevier B.V. All rights reserved.
Keywords:
Assignment problems
Combinatorial optimization
Approximation algorithms
Computational complexity
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