Abstract
After decades of intensive research on the vehicle routing problem (VRP), many highly efficient single‐objective heuristics exist for a multitude of VRP variants. But when new side‐objectives emerge—such as service quality, workload balance, pollution reduction, consistency—the prevailing approach has been to develop new, problem‐specific, and increasingly complex multiobjective (MO) methods. Yet in principle, MO problems can be efficiently solved with existing single‐objective solvers. This is the fundamental idea behind the well‐known ϵ‐constraint method (ECM). Despite its generality and conceptual simplicity, the ECM has been largely ignored in the domain of heuristics and remains associated mostly with exact algorithms. In this article, we dispel these preconceptions and demonstrate that ϵ‐constraint‐based frameworks can be a highly effective way to directly leverage the decades of research on single‐objective VRP heuristics in emerging MO settings.
| Originalsprache | Englisch |
|---|---|
| Seiten (von - bis) | 382-400 |
| Seitenumfang | 19 |
| Fachzeitschrift | Networks (New York): an international journal |
| Jahrgang | 73 |
| Ausgabenummer | 4 |
| DOIs | |
| Publikationsstatus | Veröffentlicht - Juni 2019 |
| Veranstaltung | Workshop on Route Optimization/Vehicle Routing (ROVER) - Warsaw, Polen Dauer: 12 Juni 2017 → 13 Dez. 2017 |
ÖFOS 2012
- 101015 Operations Research
- 502017 Logistik
Schlagwörter
- MR
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EURO 2018
Matl, P. (Teilnehmer*in)
8 Juli 2018 → 11 Juli 2018Aktivität: Wissenschaftliche Veranstaltungen › Teilnahme an ...
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12th Metaheuristics International Conference (MIC 2017)
Matl, P. (Teilnehmer*in)
4 Juli 2017 → 7 Juli 2017Aktivität: Wissenschaftliche Veranstaltungen › Teilnahme an ...
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