A Fast Exact Algorithm for the Resource Constrained Shortest Path Problem

Ahmadi, Sina; Tack, Guido; Harabor, Daniel; Kilby, Philip

doi:10.1609/aaai.v35i14.17450

Cited by 10 publications

(22 citation statements)

References 13 publications

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“…As each individual search in WC-BA* is complete, partial paths are no longer stored. Besides the early solution update (ESU) method we proposed in Ahmadi et al [5], WC-BA* has a unique method called heuristic tuning, which allows the search to improve its initial lower bounds during the search. We evaluated WC-BA* on very large graphs and compared its performance against the recent algorithms in the literature, including • WC-A*: The adapted version of the bi-objective A* search algorithm (BOA*) originally presented by Ulloa et al [34] and enhanced by us in Ahmadi et al [2].…”

Section: Background and Selected Algorithmsmentioning

confidence: 99%

“…Our adapted algorithm WC-A* leverages improvements proposed for BOA*. • WC-EBBA* par : WC-EB The extended version of our recent WC-EBBA* algorithm for the WCSPP [5], improved with parallelism. In contrast to the standard WC-EBBA* algorithm where the search only explores one direction at a time, the new variant provides the algorithm with the opportunity of executing its forward and backward searches concurrently.…”

Section: Background and Selected Algorithmsmentioning

confidence: 99%

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Enhanced methods for the weight constrained shortest path problem

Ahmadi,

Tack,

Harabor

et al. 2024

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The classic problem of constrained pathfinding is a well‐studied, yet challenging, network optimization problem with a broad range of applications in various areas such as communication and transportation. The weight constrained shortest path problem (WCSPP), the base form of constrained pathfinding with only one side constraint, aims to plan a cost‐optimum path with limited weight/resource usage. Given the bi‐criteria nature of the problem (i.e., dealing with the cost and weight of paths), methods addressing the WCSPP have some common properties with bi‐objective search. This article leverages the recent state‐of‐the‐art techniques in both constrained pathfinding and bi‐objective search and presents two new solution approaches to the WCSPP on the basis of A* search, both capable of solving hard WCSPP instances on very large graphs. We empirically evaluate the performance of our algorithms on a set of large and realistic problem instances and show their advantages over the state‐of‐the‐art algorithms in both time and space metrics. This article also investigates the importance of priority queues in constrained search with A*. We show with extensive experiments on both realistic and randomized graphs how bucket‐based queues without tie‐breaking can effectively improve the algorithmic performance of exhaustive A*‐based bi‐criteria searches.

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Section: Background and Selected Algorithmsmentioning

confidence: 99%

Section: Background and Selected Algorithmsmentioning

confidence: 99%

Enhanced methods for the weight constrained shortest path problem

Ahmadi,

Tack,

Harabor

et al. 2024

Networks

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“…The selected algorithms are the recent B&B method BiPulse (Cabrera et al 2020), the path ranking method CSP (Sedeño-Noda and Alonso-Rodríguez 2015), and our WC-EBBA* algorithm in (Ahmadi et al 2021c).…”

Section: Empirical Analysismentioning

confidence: 99%

“…Their results show that BiPulse delivers better performance than both Pulse and RC-BDA* on medium-size instances, while leaving 3% of the instances unsolved after four hours of runtime. More recently, we improved RC-BDA* of Thomas, Calogiuri, and Hewitt (2019) for the WCSPP in (Ahmadi et al 2021c) and proposed a dynamic programming framework called WC-EBBA* that can solve all instances of Sedeño-Noda and Alonso-Rodríguez (2015) within 10 minutes. In contrast to RC-BDA*, WC-EBBA* allows the search frontiers to meet at any fraction of the resource budget (not just at the 50% half-way point).…”

Section: Introductionmentioning

confidence: 99%

Weight Constrained Path Finding with Bidirectional A*

Ahmadi

Tack

Harabor

et al. 2022

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Weight constrained path finding, known as a challenging variant of the classic shortest path problem, aims to plan cost optimum paths whose weight/resource usage is limited by a side constraint. Given the bi-criteria nature of the problem (i.e., the presence of cost and weight), solutions to the Weight Constrained Shortest Path Problem (WCSPP) have some properties in common with bi-objective search. This paper leverages the state-of-the-art bi-objective search algorithm BOBA* and presents WC-BA*, an exact A*-based WCSPP method that explores the search space in different objective orderings bidirectionally. We also enrich WC-BA* with two novel heuristic tuning approaches that can significantly reduce the number of node expansions in the exhaustive search of A*. The results of our experiments on a large set of realistic problem instances show that our new algorithm solves all instances and outperforms the state-of-the-art WCSPP algorithms in various scenarios.

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“…Figure 1: An example graph with cost on the edges bounded A* (Ahmadi et al 2021b). For a further speedup we exploit already computed heuristic values.…”

Section: Initialisation Phasementioning

confidence: 99%

Bi-Objective Search with Bi-directional A* (Extended Abstract)

Ahmadi

Tack

Harabor

et al. 2021

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Bi-objective search is a problem of finding a set of optimal solutions in a two-dimensional domain. This study proposes several enhancements to the state-of-the-art bi-objective search with A* and develops its bi-directional variant. Our experimental results on benchmark instances show that our enhanced algorithm is on average five times faster than the state of the art bi-objective search algorithms.

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A Fast Exact Algorithm for the Resource Constrained Shortest Path Problem

Cited by 10 publications

References 13 publications

Enhanced methods for the weight constrained shortest path problem

Enhanced methods for the weight constrained shortest path problem

Weight Constrained Path Finding with Bidirectional A*

Bi-Objective Search with Bi-directional A* (Extended Abstract)

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