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A benchmark dataset for the multiple depot vehicle scheduling problem.

ABSTRACT: This data article presents a description of a benchmark dataset for the multiple depot vehicle scheduling problem (MDVSP). The MDVSP is to assign vehicles from different depots to timetabled trips to minimize the total cost of empty travel and waiting. The dataset has been developed to evaluate the heuristics of the MDVSP that are presented in "A new formulation and a column generation-based heuristic for the multiple depot vehicle scheduling problem" (Kulkarni et al., 2018). The dataset contains 60 problem instances of varying size. Researchers can use the dataset to evaluate the future algorithms for the MDVSP and compare the performance with the existing algorithms. The dataset includes a program that can be used to generate new problem instances of the MDVSP.

SUBMITTER: Kulkarni S

PROVIDER: S-EPMC6312793 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature

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A benchmark dataset for the multiple depot vehicle scheduling problem.

Kulkarni Sarang S Krishnamoorthy Mohan M Ranade Abhiram A Ernst Andreas T AT Patil Rahul R

Data in brief 20181218

This data article presents a description of a benchmark dataset for the multiple depot vehicle scheduling problem (MDVSP). The MDVSP is to assign vehicles from different depots to timetabled trips to minimize the total cost of empty travel and waiting. The dataset has been developed to evaluate the heuristics of the MDVSP that are presented in "A new formulation and a column generation-based heuristic for the multiple depot vehicle scheduling problem" (Kulkarni et al., 2018). The dataset contain ...[more]

PMID: 30619926

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