A benchmark dataset for the multiple depot vehicle scheduling problem

被引：0

作者：

Kulkarni, Sarang ^{[1
,2
,3
]}

Krishnamoorthy, Mohan ^{[4
,5
]}

Ranade, Abhiram ^{[6
]}

Ernst, Andreas T. ^{[3
]}

Patil, Rahul ^{[2
]}

机构：

[1] Indian Inst Technol, IITB Monash Res Acad, Mumbai 400076, Maharashtra, India

[2] Indian Inst Technol, SJM Sch Management, Mumbai 400076, Maharashtra, India

[3] Monash Univ, Sch Math Sci, Clayton, Vic 3800, Australia

[4] Monash Univ, Dept Mech & Aerosp Engn, Clayton, Vic 3800, Australia

[5] Univ Queensland, Sch Informat Technol & Elect Engn, Brisbane, Qld 4072, Australia

[6] Indian Inst Technol, Dept Comp Sci & Engn, Mumbai 400076, Maharashtra, India

来源：

DATA IN BRIEF | 2019年 / 22卷

关键词：

D O I：

10.1016/j.dib.2018.12.055

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

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. (C) 2018 Published by Elsevier Inc.

引用

页码：484 / 487

页数：4

共 50 条

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