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Computing the sequence of k-cardinality assignments

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  • Amnon Rosenmann

    (Graz University of Technology)

Abstract

The k-cardinality assignment (k-assignment, for short) problem asks for finding a minimal (maximal) weight of a matching of cardinality k in a weighted bipartite graph $$K_{n,n}$$ K n , n , $$k \le n$$ k ≤ n . Here we are interested in computing the sequence of all k-assignments, $$k=1,\ldots ,n$$ k = 1 , … , n . By applying the algorithm of Gassner and Klinz (2010) for the parametric assignment problem one can compute in time $${\mathcal {O}}(n^3)$$ O ( n 3 ) the set of k-assignments for those integers $$k \le n$$ k ≤ n which refer to essential terms of the full characteristic maxpolynomial $${\bar{\chi }}_{W}(x)$$ χ ¯ W ( x ) of the corresponding max-plus weight matrix W. We show that $${\bar{\chi }}_{W}(x)$$ χ ¯ W ( x ) is in full canonical form, which implies that the remaining k-assignments refer to semi-essential terms of $${\bar{\chi }}_{W}(x)$$ χ ¯ W ( x ) . This property enables us to efficiently compute in time $${\mathcal {O}}(n^2)$$ O ( n 2 ) all the remaining k-assignments out of the already computed essential k-assignments. It follows that time complexity for computing the sequence of all k-cardinality assignments is $${\mathcal {O}}(n^3)$$ O ( n 3 ) , which is the best known time for this problem.

Suggested Citation

  • Amnon Rosenmann, 2022. "Computing the sequence of k-cardinality assignments," Journal of Combinatorial Optimization, Springer, vol. 44(2), pages 1265-1283, September.
  • Handle: RePEc:spr:jcomop:v:44:y:2022:i:2:d:10.1007_s10878-022-00889-4
    DOI: 10.1007/s10878-022-00889-4
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    References listed on IDEAS

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    1. Volgenant, A., 2004. "Solving the k-cardinality assignment problem by transformation," European Journal of Operational Research, Elsevier, vol. 157(2), pages 322-331, September.
    2. H. W. Kuhn, 1956. "Variants of the hungarian method for assignment problems," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 3(4), pages 253-258, December.
    3. Asoke Kumar Bhunia & Amiya Biswas & Subhra Sankha Samanta, 2017. "A genetic algorithm-based approach for unbalanced assignment problem in interval environment," International Journal of Logistics Systems and Management, Inderscience Enterprises Ltd, vol. 27(1), pages 62-77.
    4. H. W. Kuhn, 1955. "The Hungarian method for the assignment problem," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 2(1‐2), pages 83-97, March.
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