• Journal of the Korea Society of Computer and Information
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• v.21 no.1
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• pp.131-138
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• 2016

In this paper, we propose a simple linear bottleneck assignment problems (LBAP) algorithm to find the optimal solution. Generally, the LBAP has been solved by threshold or augmenting path algorithm. The primary characteristic of proposed algorithm is derived the optimal solution of LBAP from linear sum assignment problem (LSAP). Firstly, we obtains the solution for LSAP from the selected minimum cost of rows and moves the duplicated costs in row to unselected row with minimum increasing cost in direct and indirect paths. Then, we obtain the optimal solution of LBAP according to the maximum cost of LSAP can be move to less cost. For the 29 balanced and 7 unbalanced problem, this algorithm finds optimal solution as simple.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.6
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• pp.211-220
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• 2013

This paper proposes an algorithm that easily finds an optimal solution for linear bottleneck assignment problems. It is either threshold or augmenting path algorithm that is generally used to solve the bottleneck assignment problem. This paper proposes a reverse-delete algorithm that follows 2 steps. Firstly, the algorithm deletes the maximum cost in a given matrix until it renders a single row or column. Next, the algorithm improves any solution that contains a cost exceeding the threshold value $c^*_{ij}$. Upon its application to 28 balanced assignment problems and 7 unbalanced problems, the algorithm is found to be both successful and simple.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.5
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• pp.159-164
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• 2022

The linear assignment problem (LAP) and linear bottleneck assignment problem (LBAP) has been unknown the algorithm to solve the optimal solution within polynomial-time. These problems are classified by NP-hard. Therefore, we can be apply metaheuristic methods or linear programming (LP) software package or Hungarian algorithm (HA) with O(m⁴) computational complexity. This paper suggests polynomial time algorithm with O(mn)=O(m²),m=n time complexity to LAP and LBAP. The select-delete method is simply applied to LAP, and the delete-select method is used to LBAP. For the experimental data without the unique algorithm can be apply to whole data, the proposed algorithm can be obtain the optimal solutions for whole data.