No abstract

R ail transportation has experienced a rebirth in the last few decades, and a very large investment will certainly be made in new railway lines in the years to come-especially in high-speed rail lines. The success of such investment is heavily dependent on rail ridership, which in turn is dependent on the location of railway stations. In this paper, we present a mixed-integer optimization model that determines the optimal location (and number) of stations along a railway line that will be introduced over an existing transportation network. The stations are chosen within a set of possible locations defined a priori according to the objective of maximizing travel cost savings. The model takes into account the sensitivity of rail ridership to time losses because of stops at intermediate stations, as well as (static) competition from other modes. The practical usefulness of the model is illustrated with a case study involving a high-speed rail line expected to be built in Portugal in the future: the Lisbon-Porto line.

No abstract

Article Info AbstractKeywords: Airport Logistics Check-in Counter Allocation Problem Optimization Models Simulation This paper presents a new methodology to optimize the Airport Check-in Counter Allocation Problem. The methodology combines optimization, simulation and adjacent resource scheduling and aims to determine the optimal number, location and schedule of check-in desks to open for departing flights, such that operational costs are minimized and a given service level is ensured. The methodology is composed of three steps.Step 1 uses optimization models to determine the optimal number of desks.Step 2 uses simulation to assess if the first step results meet the overall service level.Step 3 uses an optimization model to enforce the adjacent constraint. The paper focus then onStep 1, to which we present two new optimization models for common and dedicated check-in systems which include a service level constraint. Finally, these models are applied to a case study with actual data. We conclude the best time interval length should be 30 minutes or less and, as expected, the dedicated system requires, in general, more desks than the common system. Additionally, the results demonstrate the accuracy of the models to reach the trade-off between the operational costs and a given service level.

No abstract

No abstract

No abstract

No abstract