Year: 2026
Type: article
Abstract: ABSTRACT The dynamic capacitated arc routing problem (DCARP) aims to update the service paths of vehicles in the capacitated arc routing problem when uncertain factors deteriorate the current schedule of vehicles' services. A DCARP scenario comprises a series of DCARP instances that share similarities with each other. Therefore, optimisation experience gained from solving the former DCARP instance can potentially facilitate the optimisation for a new DCARP instance. However, existing optimisation algorithms for solving DCARP seldom consider such optimisation experience and instead re‐optimise the DCARP instance from scratch. This paper proposes a dynamic optimisation framework with a solution building block adaptation strategy (DO‐SBBA) that extracts the optimisation experience from the former optimisation process to facilitate the optimisation of the next DCARP instance. The framework introduces the concept of building blocks for extracting the valuable experience contained in historical solutions. The building block‐based constructive heuristic is proposed to handle DCARP scenarios with cost‐ or task‐changing dynamic events, and an insertion heuristic is proposed to handle task‐changing dynamic events. Experimental studies demonstrate the effectiveness of DO‐SBBA for extracting and utilising optimisation experience in DCARP scenarios, significantly improving the performance of dynamic optimisation compared to state‐of‐the‐art DCARP methods.
DOI: 10.1049/cit2.70106
Institutions: Lingnan University, University of Birmingham, Honda (Germany)
Language: English
Subfield: Industrial and Manufacturing Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,760
Awards: G1308942226, G8435032178, G8555519613
OpenAlex ID: W7127562699