The Restricted Inverse Optimal Value Problem under Weighted Bottle-neck Hamming distance on trees

TL;DR

This paper introduces efficient algorithms with $O(n ext{log} n)$ complexity for solving the Restricted Inverse Optimal Value Problem on trees under weighted bottleneck Hamming distance, including a related shortest path interdiction problem.

Contribution

It develops the first polynomial-time algorithms for RIOVSPT$_{BH}$ and MCSPIT problems on trees under weighted bottleneck Hamming distance, with proven efficiency.

Findings

Algorithms run in $O(n\log n)$ time.

Computational experiments confirm effectiveness.

Structural analysis aids algorithm development.

Abstract

We consider the Restricted Inverse Optimal Value Problem (RIOVSP) on trees under weighted bottleneck Hamming distance, denoted as (RIOVSPT$_{BH}$). The problem aims to minimize the total cost under weighted bottle-neck Hamming distance such that the length of the shortest root-leaf path of the tree is lower-bounded by a given value by adjusting the length of some edges. Additionally, the specified lower bound must correspond to the length of a particular root-leaf path. Through careful analysis of the problem's structural properties, we develop an algorithm with $O(n\log n)$ time complexity to solve (RIOVSPT$_{BH}$). Furthermore, by removing the path-length constraint, we derive the Minimum Cost Shortest Path Interdiction Problem on Trees (MCSPIT), for which we present an $O(n\log n)$ time algorithm that operates under weighted bottleneck Hamming distance. Extensive computational experiments demonstrate the efficiency and effectiveness of both algorithms.