From One Solution to Many: An Oracle-Based FPT Framework for Diverse Solutions under Generalized Diversity Measures
Pradeesha Ashok, Sobyasachi Chatterjee, Soumi Nandi, Saket Saurabh, Priyanshu Tiwari
Abstract
The problem of computing diverse solutions has recently emerged as an important area of study, motivated by applications in fairness, robustness, and security. Instead of returning a single feasible or optimal solution, the goal is to output a collection of meaningfully different solutions, often measured by symmetric differences. Diverse variants have been studied using sparsification, network-flow reductions, and algebraic techniques. We investigate the fixed-parameter tractability of diverse variants of an implicit set-system problem. Given parameters k and r and a threshold b, the task is to compute r feasible solutions, each of size at most k, whose diversity under a specified objective is at least b. Our main contribution is an oracle-based meta-theorem. We identify a broad class of objectives, called consistently diverse, that includes several standard measures. Assuming an exact empty-extension oracle given a forbidden set Forb, which returns a feasible solution of a prescribed size avoiding Forb or reports that none exists, we obtain a fixed-parameter tractable algorithm parameterized by k+r. The algorithm makes at most (2kr)kr · r oracle calls, and in each call the oracle parameter satisfies s+| Forb| ≤ k+2kr. Our framework unifies and strengthens previous oracle-based approaches. Compared with Kumabe's framework (ESA 2025), which gives a doubly exponential bound on the number of oracle calls, our approach achieves the single exponential bound 2O(kr(kr)) and directly constructs the desired tuple of solutions. We recover fixed-parameter tractable algorithms for all problems covered by that framework, with improved oracle complexity, and obtain strong bounds for diverse variants of classical graph and matroid problems.
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