AIApr 15, 2020

Ants can orienteer a thief in their robbery

arXiv:2004.07017v32 citations
AI Analysis

This work addresses a specific optimization problem for researchers in combinatorial algorithms, but it is incremental as it builds on existing Ant Colony Optimization methods.

The authors tackled the Thief Orienteering Problem, a complex combinatorial optimization challenge, by developing an Ant Colony Optimization algorithm with a new packing heuristic, achieving an average improvement of over 300% and outperforming existing methods on more than 90% of benchmark instances.

The Thief Orienteering Problem (ThOP) is a multi-component problem that combines features of two classic combinatorial optimization problems: Orienteering Problem and Knapsack Problem. The ThOP is challenging due to the given time constraint and the interaction between its components. We propose an Ant Colony Optimization algorithm together with a new packing heuristic to deal individually and interactively with problem components. Our approach outperforms existing work on more than 90% of the benchmarking instances, with an average improvement of over 300%.

Code Implementations1 repo
Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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