Pseudo-random Instance Generators in C++ for Deterministic and Stochastic Multi-commodity Network Design Problems

TL;DR

This paper introduces two high-speed pseudo-random instance generators in C++ for deterministic and stochastic multi-commodity network design problems, enabling systematic testing and promoting reproducibility in research.

Contribution

The paper presents novel, flexible generators for MCFNDP problems, facilitating large-scale experimentation and comparison of solution methods in both deterministic and stochastic contexts.

Findings

Generators enable rapid creation of diverse problem instances

Facilitate thorough evaluation of algorithms' performance

Support reproducibility and comparability in research

Abstract

Network design problems constitute an important family of combinatorial optimization problems for which numerous exact and heuristic algorithms have been developed over the last few decades. Two central problems in this family are the multi-commodity, capacitated, fixed charge network design problem (MCFNDP) and its stochastic counterpart, the two-stage MCFNDP with recourse. These are standard problems that often serve as work benches for devising and testing models and algorithms in stylized but close-to-realistic settings. The purpose of this paper is to introduce two flexible, high-speed generators capable of simulating a wide range of settings for both the deterministic and stochastic MCFNDPs. We hope that, by facilitating systematic experimentation with new and larger sets of instances, these generators will lead to a more thorough assessment of the performance achieved by exact and heuristic solution methods in both deterministic and stochastic settings. We also hope that making these generators available will promote the reproducibility and comparability of published research.