The importance of mobility and logistics has steadily increased in recent years. Today, this sector represents a significant part of economic output, but also of resource consumption. In order to achieve the ambitious environmental and climate protection goals, there is a high demand for innovative concepts.
In this area we focus on bike and car sharing. They offer considerable potential for saving fossil fuels, particularly in combination with local and long-distance public transport. In recent years, public bicycle rental systems have emerged in many cities around the world. These systems allow automatic rental and return of bicycles at a large number of stations. Modern Car-Sharing providers enable borrowing and returning at almost any parking space within a defined business area (free-floating). We concentrate on the following questions of strategic planning and dimensioning of the systems as well as operations and cooperate with a well-known German free-floating Car-Sharing provider:
Bike sharing has been introduced in many cities, often by municipalities and is nowadays an established alternative for other short-distance transport systems. However, in cities with high elevations, the usual bike-sharing systems face a severe problem. Resulting from an imbalance of demand, the number of bikes at stations at elevated locations decreases during the day, while it increases at stations at lower locations. This situation poses a challenge for the relocation process because high numbers of bicycles have to be transported to the stations at elevated locations in order to achieve a suitable starting point for the next period. With the usage of e-bike sharing-systems, this problem can be circumvented because e-bikes facilitate the mobility in elevated and steep terrains. This paper considers an e-bike sharing-system with removable batteries. In the first step, a deterministic Mixed-Integer Linear Program (MILP) calculates the optimal route for trucks and the optimal initial distribution of bikes. In the second step, a stochastic simulation should evaluate these results.
Airlines today are exposed to high pressure on costs, which will continue to rise as a result of the CO2 tax, for example. This forces them to use their capacities efficiently. The precondition for this is a flight schedule that is as attractive as possible for potential passengers, both in terms of the connections and the flight times. The design of corresponding flight schedules at the medium-term planning level is an extremely complex decision-making problem that can only be successfully tackled with the aid of quantitative methods.
The project focuses on the following two aspects:
Optimizing an airline schedule usually comprises multiple planning stages. These are the choice of flights to offer (schedule design), the assignment of fleets to flight legs (fleet assignment), and the construction of rotations under consideration of maintenance constraints (aircraft maintenance routing). Moreover, the airline must assign crews to all flights (crew scheduling). Traditionally, either these scheduling stages are considered sequentially or an existing schedule is modified to cope with the arising complexity issue. More recently, some authors have developed models that integrate adjacent stages. In this paper, outcomes of a research project with airline information technology provider Lufthansa Systems are presented. We consider the case of a small to medium-sized point-to-point airline with a homogeneous fleet. Hence, fleet assignment is omitted, which offers the possibility to solve schedule design and aircraft maintenance routing simultaneously. Our approach explicitly accounts for passengers’ return flight demand and for marginal revenues declining with increasing seat capacity, hence, anticipating the effects of capacity control in revenue management systems. To solve the arising integrated mixed-integer problem, a branch-and-price approach and a column generation-based heuristic have been developed. An extensive numerical study, using data from a major European airline provided by Lufthansa Systems, shows that the presented approaches yield high-quality solutions to real-world problem instances within a reasonable time.