Shangyao Yan

Optimal scheduling of emergency roadway repair and subsequent relief distribution

Emergency roadway repair and relief distribution planning following a natural disaster has traditionally been done manually and separately, based on the decision-makers experience, disregarding the interrelationship between emergency roadway repair and relief distribution from the system perspective, which may yield inferior solutions. Hence, in this research we consider minimizing the length of time required for both emergency roadway repair and relief distribution, as well as the related operating constraints, to develop a model, for planning emergency repair and relief distribution routes and schedules within a limited time. We construct a time-space network for emergency repair and another for relief distribution. A number of operational constraints are set between these two networks according to real constraints. Our model is a multi-objective, mixed-integer, multiple-commodity network flow problem. We adopt the weighting method and develop a heuristic to efficiently solve this problem in practice. To evaluate our model and the solution algorithm, we perform a case study. The results show the model and the solution algorithm could be useful in practice.

A SCHEDULING MODEL AND A SOLUTION ALGORITHM FOR INTER-CITY BUS CARRIERS

Abstract The setting of timetables and bus routing/scheduling are essential to an inter-city bus carriers profitability, its level of service and its competitive capability in the market. In the past, carriers in Taiwan usually set their timetables and bus routes/schedules manually, which was inefficient. In this research we thus attempt to develop a model that will help Taiwan inter-city bus carriers in timetable setting and bus routing/scheduling. The model employs multiple time–space networks that can formulate bus movements and passenger flows and manage the interrelationships between passenger trip demands and bus trip supplies to produce the best timetables and bus routes/schedules. Mathematically, the model is formulated as a mixed integer multiple commodity network flow problem. An algorithm, based on Lagrangian relaxation, a sub-gradient method, the network simplex method, a Lagrangian heuristic and a flow decomposition algorithm, is developed to efficiently solve the problem. The results of a case study, regarding a major Taiwan inter-city bus operation, illustrate the model performance.

Optimization of multiple objective gate assignments

This paper proposes a multiple objective model to help airport authorities to efficiently and effectively solve gate assignment problems. The model is formulated as a multiple objective zero-one integer program. To efficiently solve large-scale problems in practice, we used the weighting method, the column generation approach, the simplex method and the branch-and-bound technique to develop a solution algorithm. To test how well the model may be applied in actual operations, a case study regarding the operation of Chiang Kai-Shek (CKS) Airport was performed. The results show that the model could be useful for actual operations.

A simulation framework for evaluating airport gate assignments

There are many factors that affect gate assignments in an airports operations. These factors include static gate assignments, stochastic flight delays and real-time gate assignments. Most research on gate assignments in the past has laid stress on improving the performance of static gate assignments. None has analyzed the interrelationship between static gate assignments and real-time gate assignments as affected by the stochastic flight delays that occur in real operations. In addition, none has designed flexible buffer times for static gate assignments to effectively absorb stochastic delays in real-time gate assignments. This research proposes a simulation framework, that is not only able to analyze the effects of stochastic flight delays on static gate assignments, but can also evaluate flexible buffer times and real-time gate assignment rules. Finally, a simulation based on Chiang Kai-Shek airport operations is performed to evaluate the simulation framework.

A decision support framework for multi-fleet routing and multi-stop flight scheduling

Fleet routing and flight scheduling are important in airline carrier operations. Ineffective and inefficient fleet routing and flight scheduling will result in a substantial loss of profits. This research aims at developing a framework to help carriers adjust their draft timetables and fleet routes, when market demand conditions are expected to change in the near future. The framework is based on a basic model, constructed as a multi-fleet time-space network from which several strategic models are developed, to help carriers in fleet routing and flight scheduling. These models are formulated as multiple commodity network flow problems. The Lagrangian relaxation accompanied by the network simplex method, a Lagrangian heuristic and a modified sub-gradient method are suggested to solve the problems. A flow decomposition algorithm is also suggested in order to trace every aircraft route. To show how to apply this framework in the real world, a case study regarding the international operations of a major Taiwan airline was performed. The results show that, the framework would be useful for actual operations.

A Heuristic Approach for Airport Gate Assignments for Stochastic Flight Delays

To make good flight to gate assignments, not only do all the relevant constraints have to be considered, but stochastic flight delays that occur in actual operations also have to be taken into account. In past research, airport gate assignments and stochastic disturbances have often been handled in the planning and the real-time stages separately, meaning that the interrelationship between these stages, as affected by such delays, has been neglected. In this research, we develop a heuristic approach embedded in a framework designed to help the airport authorities make airport gate assignments that are sensitive to stochastic flight delays. The framework includes three components, a stochastic gate assignment model, a real-time assignment rule, and two penalty adjustment methods. The test results are based on data supplied by a Taiwan international airport, and show that the proposed framework performs better than the current manual assignment process and the traditional deterministic model.

A passenger demand model for airline flight scheduling and fleet routing

Fleet routing and flight scheduling are essential to a carriers profitability, its level of service and its competitive capability in the market. This research develops a model and a solution algorithm to help carriers simultaneously solve for better fleet routes and appropriate timetables. The model is formulated as an integer multiple commodity network flow problem. An algorithm based on Lagrangian relaxation, a sub-gradient method, the network simplex method, the least cost flow augmenting algorithm and the flow decomposition algorithm is developed to efficiently solve the problem. The results of a case study, regarding a major Taiwan airlines operations, show the models good performance.

Multifleet routing and multistop flight scheduling for schedule perturbation

Efficient and effective incidental scheduling techniques for schedule perturbation are essential to an airline carriers operations. This research aims at developing a framework to assist carriers in fleet routing and flight scheduling for schedule perturbations in the operations of multifleet and multistop flights. The framework is based on a basic multifleet schedule perturbation model constructed as a timespace network from which strategic models are developed to research incidental scheduling. These network models are formulated as multiple commodity network flow problems. Lagrangian relaxation with subgradient methods accompanied by the network simplex method, a Lagrangian heuristic and a modified subgradient method are developed to solve the problems. A case study regarding the international operations of a major Taiwan airline carrier is presented.

A network model for airline cabin crew scheduling

Abstract Airline crew scheduling problems have been traditionally formulated as set covering problems or set partitioning problems. When flight networks are extended, these problems become more complicated and thus more difficult to solve. From the current practices of a Taiwan airline, whose work rules are relatively simple compared to many airlines in other countries, we find that pure network models, in addition to traditional set covering (partitioning) problems, can be used to formulate their crew scheduling problems. In this paper, we introduce a pure network model that can both efficiently and effectively solve crew scheduling problems for a Taiwan airline using real constraints. To evaluate the model, we perform computational tests concerning the international line operations of a Taiwan airline.

Airline cockpit crew scheduling

Abstract Essential to airline operations, cockpit crew scheduling has not been researched much in the past. In this research we developed a model and two scheduling networks, using real data from a Taiwan airline, to help minimize cockpit crew costs and to plan for proper cockpit crew pairings. The model was formulated as a set-partitioning problem. A column generation approach was proposed to efficiently solve the problem. To show how well the model could be applied to the real world, a case study regarding the international operations of a Taiwan airline was performed.