A central element of the air cargo planning process is the generation of optimal flight schedules. A flight schedule simultaneously defines the market potential of an airline and allocates its resources. The schedule design process is a difficult and time-consuming task that involves and affects virtually all business units. Because of its complexity, the process is traditionally decomposed into several steps that are executed in a sequential manner. In this paper, we present novel model formulations and solution procedures which have been developed in the course of a feasibility study for a decision support system (DSS) for a pragmatic approach to "freighter network planning" at one of the top international cargo carriers. We formulate two integrated models that combine the three planning steps: flight selection, aircraft rotation planning, and cargo routing. The aim of the schedule optimization is to maximize the network-wide profit by determining the best combination from a list of mandatory and optional flights, assigning the selected flights to aircrafts and identifying optimal cargo flows. Both model formulations are embedded in a solution procedure that builds on the column generation technique with shortest path algorithms for solving the subproblems. The applicability of the models in a DSS is demonstrated on realistic problem instances that match the requirements specified in the feasibility study.
This paper reports the results of a joint project with a large railway company in Germany to build a decision support system for analyzing the consequences of timetable changes, modifications of break and working time regulations as well as changes in the cost structure on future crew needs. For that purpose we have developed a mathematical model of the underlying crew scheduling problem that respects all the organizational and technical constraints as well as labor regulations. We have implemented a Branch&Price based optimization system that is used to perform scenario analyses of future crew needs using medium-term timetable drafts as input data.Keywords Railway crew scheduling · Break and working time regulations · Branch and price · Decision support system
Crew scheduling is a highly complex combinatorial problem that has substantial and consequential economic importance in practice. Although the core structure of the problem is the same in many different areas like urban transportation, airlines etc, the specific problem instances show significant differences with respect to constraints stemming from different legal, industry-wide and firm-specific regulations. Beasley and Cao (1996) have introduced a generic crew scheduling problem (GCSP) and a basic mathematical program. In this paper, we extend this work by introducing two types of GCSPs that represent important additional features arising in real-world settings: the possibility of deadheading and the partitioning into duties with long (overnight) breaks in between. We present appropriate models, outline the design of a common branch and price and cut-solution approach and report computational experience. The aim of this study is to analyse the additional complexity that occurs by introducing these concepts, as well as the reduction in operational cost that can be obtained.
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