A Multi-Depot Vehicle Routing Problem with Stochastic Road Capacity and Reduced Two-Stage Stochastic Integer Linear Programming Models for Rollout Algorithm Article Swipe
Wadi Khalid Anuar
,
Lai Soon Lee
,
Hsin‐Vonn Seow
,
Stefan Pickl
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.3390/math9131572
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.3390/math9131572
A matheuristic approach based on a reduced two-stage Stochastic Integer Linear Programming (SILP) model is presented. The proposed approach is suitable for obtaining a policy constructed dynamically on the go during the rollout algorithm. The rollout algorithm is part of the Approximate Dynamic Programming (ADP) lookahead solution approach for a Markov Decision Processes (MDP) framed Multi-Depot Dynamic Vehicle Routing Problem with Stochastic Road Capacity (MDDVRPSRC). First, a Deterministic Multi-Depot VRP with Road Capacity (D-MDVRPRC) is presented. Then an extension, MDVRPSRC-2S, is presented as an offline two-stage SILP model of the MDDVRPSRC. These models are validated using small simulated instances with CPLEX. Next, two reduced versions of the MDVRPSRC-2S model (MDVRPSRC-2S1 and MDVRPSRC-2S2) are derived. They have a specific task in routing: replenishment and delivering supplies. These reduced models are to be utilised interchangeably depending on the capacity of the vehicle, and repeatedly during the execution of rollout in reinforcement learning. As a result, it is shown that a base policy consisting of an exact optimal decision at each decision epoch can be obtained constructively through these reduced two-stage stochastic integer linear programming models. The results obtained from the resulting rollout policy with CPLEX execution during rollout are also presented to validate the reduced model and the matheuristic algorithm. This approach is proposed as a simple implementation when performing rollout for the lookahead approach in ADP.
Related Topics
Concepts
Integer programming
Linear programming
Mathematical optimization
Markov decision process
Vehicle routing problem
Dynamic programming
Routing (electronic design automation)
Integer (computer science)
Stochastic programming
Computer science
Branch and price
Stochastic modelling
Markov process
Mathematics
Computer network
Programming language
Statistics
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/math9131572
- https://www.mdpi.com/2227-7390/9/13/1572/pdf?version=1625483840
- OA Status
- gold
- Cited By
- 12
- References
- 68
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3178514907
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3178514907Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/math9131572Digital Object Identifier
- Title
-
A Multi-Depot Vehicle Routing Problem with Stochastic Road Capacity and Reduced Two-Stage Stochastic Integer Linear Programming Models for Rollout AlgorithmWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2021Year of publication
- Publication date
-
2021-07-04Full publication date if available
- Authors
-
Wadi Khalid Anuar, Lai Soon Lee, Hsin‐Vonn Seow, Stefan PicklList of authors in order
- Landing page
-
https://doi.org/10.3390/math9131572Publisher landing page
- PDF URL
-
https://www.mdpi.com/2227-7390/9/13/1572/pdf?version=1625483840Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
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https://www.mdpi.com/2227-7390/9/13/1572/pdf?version=1625483840Direct OA link when available
- Concepts
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Integer programming, Linear programming, Mathematical optimization, Markov decision process, Vehicle routing problem, Dynamic programming, Routing (electronic design automation), Integer (computer science), Stochastic programming, Computer science, Branch and price, Stochastic modelling, Markov process, Mathematics, Computer network, Programming language, StatisticsTop concepts (fields/topics) attached by OpenAlex
- Cited by
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12Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 2, 2024: 4, 2022: 6Per-year citation counts (last 5 years)
- References (count)
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68Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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