Short-Term Scientific Mission

Modular Algorithm Components for Combinatorial Optimisation within the ROAR-NET API

Main theme: Algorithm Selection and Configuration
Grantee: Kazım Erdoğdu, Yaşar Üniversitesi, Izmir, Türkiye
Host: Alexandros Tzanetos, Jönköping University, Jönköping, Sweden

Start date: 2026-05-18
End date: 2026-06-06
Awarded: 2026-03-29
Report approved: 2026-07-28

Description

Randomised Optimisation Algorithms (ROAs) are widely used to solve complex optimisation problems in domains such as logistics, manufacturing, and transportation. Their performance strongly depends on the design and interaction of key algorithmic components such as neighbourhood operators, mutation and recombination mechanisms, and local search procedures. This STSM aims to investigate these modular algorithm components and integrate them into the ROAR-NET API in a reusable and configurable way. The work will involve implementing selected components within the ROAR-NET API and evaluating their behaviour on representative benchmark instances of the Vehicle Routing Problem (VRP) and its variants. Through systematic experimentation, the study will analyse how different combinations of algorithm components influence optimisation performance. The outcomes will contribute to the development of flexible optimisation infrastructures and support ongoing efforts within ROAR-NET to enable modular algorithm design and reproducible experimentation.

Achievements

The STSM substantially achieved its objectives by defining and modularly implementing key genetic algorithm components for the Capacitated VRP, including crossover, mutation, selection, solution representation, and vehicle-splitting operators. The produced code was specifically designed to fit the architecture and interface structure of the ROAR-NET API, supporting reuse, configuration, and future extension to other randomised optimisation algorithms. The components were evaluated on representative CVRPLIB benchmark instances, while hyperparameter tuning and a full factorial design of experiments were used to analyse their effects on convergence and population diversity. A concise user manual documenting the implemented components and their usage was also produced.