Chia-Hung Chen

Optimal flight scheduling models for cargo airlines under alliances

Abstract In this paper we develop several coordinated scheduling models combining airport selection, fleet routing and timetable setting, in order to help airlines solve for the most satisfactory cargo fleet routes and timetables when they enter into alliances. We employ network flow techniques to construct the models, which are formulated as a multiple commodity network flow problem and can be solved using a mathematical programming solver. To evaluate the models, we perform numerical tests based on real operating data from two Taiwan airlines. The preliminary results are good, showing that the models would be useful for airline alliances.

Applying Lagrangian relaxation-based algorithms for airline coordinated flight scheduling problems

Yan and Chen (2007, 2008) employed network flow techniques to construct coordinated scheduling models for passenger- and cargo-transportation, respectively. These models are formulated as mixed integer multiple commodity network flow problems with side constraints (NFPWS) that are characterized as NP-hard. Problem sizes are expected to be huge making the model more difficult to solve than traditional passenger/cargo flight scheduling problems. Therefore, a family of Lagrangian based algorithm is developed to solve the coordinated fleet routing and flight scheduling problems. Numerical tests are performed to evaluate the proposed algorithm using real operating data from two Taiwan airlines. The test results indicate that these solution algorithms are a significant improvement over those obtained with CPLEX. Moreover, the Lagrangian based algorithms are better than the mixed-stop heuristic, consequently they could be useful for allied airlines to solve coordinated fleet routing and flight scheduling problems.

Short-term manpower planning for MRT carriage maintenance under mixed deterministic and stochastic demands

The purpose of this research is to develop two manpower supply planning models and a solution algorithm for mass rapid transit carriage maintenance under mixed deterministic and stochastic demands. These models are formulated as mixed integer programs that are characterized as NP-hard. We employ problem decomposition techniques, coupled with the CPLEX mathematical programming solver, to develop an algorithm that is capable of efficiently solving the problems. The models and the method used currently in actual operations are evaluated by a simulation-based evaluation method. Finally, we perform a case study using real operating data from a Taiwan MRT maintenance facility. The preliminary results are good, showing that the models could be useful for planning carriage maintenance manpower supply.

A manpower supply planning model for MRT carriage maintenance

In this study, we develop a manpower supply planning model for mass rapid transit carriage maintenance under mixed deterministic and stochastic. The model and the method used currently in actual operations are evaluated by a simulation-based evaluation method. Finally, we perform a case study using real operating data from a Taiwan MRT maintenance facility. The preliminary results are good, showing that the model could be useful for planning carriage maintenance manpower supply.

Neighborhood search algorithms with restricted infeasible solution sets–application to a transportation project evaluation problem

Abstract Using a transportation project evaluation problem as an example, in this paper we employ the local search method, the threshold accepting method, together with the combination of feasible and restricted infeasible solution sets in neighborhood searches, to develop four solution algorithms. The test results indicate that the threshold accepting algorithm and the local search algorithm, that combine feasible and restricted infeasible solution sets, can improve the conventional threshold accepting algorithm and local search algorithm, which are confined to feasible solution sets.