Solution Representations and Local Search for the bi-objective Inventory Routing Problem

TL;DR

This paper investigates how different solution representations impact the effectiveness of local search methods in solving the complex bi-objective Inventory Routing Problem, providing insights into encoding strategies.

Contribution

It offers an experimental comparison of two solution encodings, enhancing understanding of their advantages and limitations for bi-objective IRP optimization.

Findings

Comparison of two encodings reveals their respective strengths and weaknesses.

Insights into how solution representations influence local search performance.

Guidance for designing effective encodings for bi-objective IRP.

Abstract

The solution of the biobjective IRP is rather challenging, even for metaheuristics. We are still lacking a profound understanding of appropriate solution representations and effective neighborhood structures. Clearly, both the delivery volumes and the routing aspects of the alternatives need to be reflected in an encoding, and must be modified when searching by means of local search. Our work contributes to the better understanding of such solution representations. On the basis of an experimental investigation, the advantages and drawbacks of two encodings are studied and compared.