Abstract
In the transportation industry, crew management is typically decomposed into two phases: crew scheduling and crew rostering. Due to the complexity of scheduling and rostering, bus transportation is not an exception and many relevant studies do not consider both procedures simultaneously. However, such a decomposition can yield inferior schedules/rosters. To address this issue, this paper proposes an integrated scheduling and rostering model for bus drivers and devises a branch-and-price-and-cut (BPC) algorithm to solve the complex problem. The proposed solution framework is empirically applied to real-world instances with various problem sizes whose data is collected from H Bus Company located in southern Taiwan. To validate the effectiveness and evaluate the efficiency of the proposed solution framework, this paper compares the solution obtained from the BPC algorithm with that of a benchmark optimization package. The results show that the proposed BPC algorithm can solve problems with large real-world instances within a reasonable computational time. Moreover, in the numerical experiments, this paper finds that the scheduling and rostering results of the bus drivers are more sensitive to the rostering constraints. Also, the proposed integrated framework can yield a better solution than the solution from a conventional two-phase approach, which demonstrates the advantage of the integration in this paper. The proposed method provided can be employed to deal with the challenges in driver planning for bus companies.
Highlights
As the public bus transport system produces less pollution than private transport, improving the quality of bus services and encouraging their use have become significant issues with the growing importance for energy conservation and carbon emissions reduction
After generating a duty set, the driver rostering problem assigns the duties to the drivers while incorporating various practical considerations, such as driver preferences and the labor laws, which must be taken into account [4]. ese two problems are typically solved sequentially due to the significant problem complexity and computational resources required to determine a feasible schedule and roster
In the case study of two depots of the Beijing Public Transport Group, the results showed that the variable neighborhood search (VNS)-based algorithm is able to effectively reduce the total driver costs
Summary
As the public bus transport system produces less pollution than private transport, improving the quality of bus services and encouraging their use have become significant issues with the growing importance for energy conservation and carbon emissions reduction. As can be expected, the decomposition can result in inferior solutions compared to the solutions obtained from an integrated framework To address this discrepancy, the current research proposes an integrated crew scheduling and rostering formulation. Even if all the duties/columns are enumerated, solving the resulting problem is an extremely challenging task To avoid these issues, this paper first relaxes the integer constraint of the decision variables and constructs a branch-and-bound solution scheme. Is paper designs a column generation algorithm that decomposes this complicated problem into a restricted master problem (RMP) and a series of pricing subproblems. E empirical results show that the integrated framework produces a superior solution when compared to solving the scheduling and rostering subproblems sequentially. E branch-and-price-and-cut algorithm used for solving the problem is detailed in Section 4, and the empirical studies are summarized in Section 5. e final section offers the conclusions and suggestions for future research
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