The Dynamic Travelling Thief Problem: Benchmarks and Performance of Evolutionary Algorithms

04/25/2020
by   Ragav Sachdeva, et al.
10

Many real-world optimisation problems involve dynamic and stochastic components. While problems with multiple interacting components are omnipresent in inherently dynamic domains like supply-chain optimisation and logistics, most research on dynamic problems focuses on single-component problems. With this article, we define a number of scenarios based on the Travelling Thief Problem to enable research on the effect of dynamic changes to sub-components. Our investigations of 72 scenarios and seven algorithms show that – depending on the instance, the magnitude of the change, and the algorithms in the portfolio – it is preferable to either restart the optimisation from scratch or to continue with the previously valid solutions.

READ FULL TEXT
research
03/01/2019

A study of problems with multiple interdependent components - Part I

Recognising that real-world optimisation problems have multiple interdep...
research
04/14/2021

A Novel Generalised Meta-Heuristic Framework for Dynamic Capacitated Arc Routing Problems

The capacitated arc routing problem (CARP) is a challenging combinatoria...
research
07/12/2016

Populations can be essential in tracking dynamic optima

Real-world optimisation problems are often dynamic. Previously good solu...
research
05/22/2023

Vector Autoregressive Evolution for Dynamic Multi-Objective Optimisation

Dynamic multi-objective optimisation (DMO) handles optimisation problems...
research
11/11/2020

Identifying Properties of Real-World Optimisation Problems through a Questionnaire

Optimisation algorithms are commonly compared on benchmarks to get insig...
research
05/06/2019

Evolutionary Optimisation of Real-Time Systems and Networks

The design space of networked embedded systems is very large, posing cha...
research
02/10/2021

Advanced Ore Mine Optimisation under Uncertainty Using Evolution

In this paper, we investigate the impact of uncertainty in advanced ore ...

Please sign up or login with your details

Forgot password? Click here to reset