Sequence and Speed Optimization

Sequencing and timing decisions frequently arise interdependently in combinatorial optimization problems. This study concerns a speed optimization problem (SOP) that determines optimal speeds to minimize a strictly convex cost function on a fixed sequence of nodes with time window constraints and a joint routing and speed optimization problem, finding an optimal sequence of nodes and speeds on each route. The paper describes two polynomial-time algorithms for the SOP, one to solve the SOP and another to compute all possible completion times for a sequence, along with proofs of optimality, and a branch-and-price algorithm, incorporating a new dominance rule, for the joint routing and speed optimization problem. Computational experiments show the proposed algorithm achieves an average 17.5-fold improvement in computational time over the state-of-the-art for benchmark instances solved to optimality (ranging from 4.9-fold on road to 73-fold on maritime instances). History: Accepted by Andrea Lodi, Area Editor for Design & Analysis of Algorithms–Discrete. Supplemental Material: The software that supports the findings of this study is available within the paper and its Supplemental Information ( https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2024.1047 ) as well as from the IJOC GitHub software repository ( https://github.com/INFORMSJoC/2024.1047 ). The complete IJOC Software and Data Repository is available at https://informsjoc.github.io/ .

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Publication Details

Journal
INFORMS journal on computing
Published
2026-07-24
DOI
https://doi.org/10.1287/ijoc.2024.1047
Primary Topic
Vehicle Routing Optimization Methods
Type
article
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article

Sequence and Speed Optimization

Stefan Schaudt, Tolga Bektaş
INFORMS journal on computing
Vehicle Routing Optimization Methods
article

Sequence and Speed Optimization

Stefan Schaudt, Tolga Bektaş
article en

Abstract

Sequencing and timing decisions frequently arise interdependently in combinatorial optimization problems. This study concerns a speed optimization problem (SOP) that determines optimal speeds to minimize a strictly convex cost function on a fixed sequence of nodes with time window constraints and a joint routing and speed optimization problem, finding an optimal sequence of nodes and speeds on each route. The paper describes two polynomial-time algorithms for the SOP, one to solve the SOP and another to compute all possible completion times for a sequence, along with proofs of optimality, and a branch-and-price algorithm, incorporating a new dominance rule, for the joint routing and speed optimization problem. Computational experiments show the proposed algorithm achieves an average 17.5-fold improvement in computational time over the state-of-the-art for benchmark instances solved to optimality (ranging from 4.9-fold on road to 73-fold on maritime instances). History: Accepted by Andrea Lodi, Area Editor for Design & Analysis of Algorithms–Discrete. Supplemental Material: The software that supports the findings of this study is available within the paper and its Supplemental Information ( https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2024.1047 ) as well as from the IJOC GitHub software repository ( https://github.com/INFORMSJoC/2024.1047 ). The complete IJOC Software and Data Repository is available at https://informsjoc.github.io/ .

INFORMS journal on computing
University of Liverpool (GB), TU Dortmund University (DE)
Life below water
Openalex Percentile: Top 8%
Vehicle Routing Optimization Methods
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