Exact algorithms for routing electric autonomous mobile robots in intralogistics

In intralogistics and manufacturing, autonomous mobile robots (AMRs) are usually electrically powered and recharged by battery swapping or induction. We investigate AMR route planning in these settings by studying different variants of the electric vehicle routing problem with due dates (EVRPD). We consider three common recharging strategies: battery swapping, inductive recharging with full recharges, and inductive recharging with partial recharges. Moreover, we consider two different objective functions: the standard objective of minimizing the total distance traveled and the minimization of the total completion times of transport jobs. The latter is of particular interest in intralogistics, where time aspects are of crucial importance and the earliest possible completion of jobs often has priority. In this context, recharging decisions also play an essential role. For solving the EVRPD variants, we propose exact branch-price-and-cut algorithms that rely on ad-hoc labeling algorithms tailored to the respective variants. We perform an extensive computational study to generate managerial insights on the AMR route planning problem and to assess the performance of our solution approach. The experiments are based on newly introduced instances featuring typical characteristics of AMR applications in intralogistics and manufacturing and on standard benchmark instances from the literature. The detailed analysis of our results reveals that inductive recharging with partial recharges is competitive with battery swapping, while using a full-recharges strategy has considerable drawbacks in an AMR setup. • Instances with typical characteristics of autonomous transports in intralogistics. • Minimization of total completion time considering three recharging strategies. • Exact branch-price-and-cut algorithms that rely on tailored labeling algorithms. • Labeling algorithms model the tradeoff between battery level and completion time. • Inductive recharging with partial recharges is competitive with battery swapping.

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Publication Details

Journal
European Journal of Operational Research
Published
2024-12-31
DOI
https://doi.org/10.1016/j.ejor.2024.12.041
Citations
5
Primary Topic
Optimization and Search Problems
Type
article
Field-Weighted Citation Impact
1.74
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article

Exact algorithms for routing electric autonomous mobile robots in intralogistics

Timo Gschwind, Anne Meyer, Boris Amberg, D. Colling
5 citations
European Journal of Operational Research
Optimization and Search Problems
1.74
article

Exact algorithms for routing electric autonomous mobile robots in intralogistics

Timo Gschwind, Anne Meyer, Boris Amberg, D. Colling
article en
5 citations

Abstract

In intralogistics and manufacturing, autonomous mobile robots (AMRs) are usually electrically powered and recharged by battery swapping or induction. We investigate AMR route planning in these settings by studying different variants of the electric vehicle routing problem with due dates (EVRPD). We consider three common recharging strategies: battery swapping, inductive recharging with full recharges, and inductive recharging with partial recharges. Moreover, we consider two different objective functions: the standard objective of minimizing the total distance traveled and the minimization of the total completion times of transport jobs. The latter is of particular interest in intralogistics, where time aspects are of crucial importance and the earliest possible completion of jobs often has priority. In this context, recharging decisions also play an essential role. For solving the EVRPD variants, we propose exact branch-price-and-cut algorithms that rely on ad-hoc labeling algorithms tailored to the respective variants. We perform an extensive computational study to generate managerial insights on the AMR route planning problem and to assess the performance of our solution approach. The experiments are based on newly introduced instances featuring typical characteristics of AMR applications in intralogistics and manufacturing and on standard benchmark instances from the literature. The detailed analysis of our results reveals that inductive recharging with partial recharges is competitive with battery swapping, while using a full-recharges strategy has considerable drawbacks in an AMR setup. • Instances with typical characteristics of autonomous transports in intralogistics. • Minimization of total completion time considering three recharging strategies. • Exact branch-price-and-cut algorithms that rely on tailored labeling algorithms. • Labeling algorithms model the tradeoff between battery level and completion time. • Inductive recharging with partial recharges is competitive with battery swapping.

European Journal of Operational ResearchVol. 323(3)
Karlsruhe Institute of Technology (DE), FZI Research Center for Information Technology (DE), Rheinland-Pfälzische Technische Universität Kaiserslautern-Landau (DE)
Affordable and clean energy
Openalex Percentile: Top 13%
Optimization and Search Problems
1.74
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