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LINUX Cluster Project

Lehrstuhl für Operations Management


  • Name: Lehrstuhl für Operations Management
  • Address: Arcisstr. 21, 80333 München
  • Project Proposal Date: 2019-03-26 15:11:21


Es geht um die Rechenstudie für das folgende Projekt. Problem statement: Outbound baggage is transferred from the terminal or transfer flights to departing airplanes. To that end, flights have to be assigned to handling facilities, the handling has to be scheduled, which involves setting the start of the baggage handling and the start of the depletion of the central baggage storage, and baggage handlers have to be assigned to load bags into containers. Baggage handling takes place in a dynamic environment. Flight delays and unforeseen arrival times of passengers at the check-in counters require dynamically adjusting the planning during the day of operation and hence, an efficient re-planning procedure. The challenge of the planning task is exacerbated by the need for obtaining a solution in as close to real-time as possible. Approach: We propose a model formulation and a solution procedure to plan the outbound baggage handling in a rolling planning fashion which allows for considering updates of problem parameters at each decision epoch. To increase the tractability of the problem, we propose a Dantzig-Wolfe decomposition and employ a column generation based heuristic to quickly generate a robust plan. Results & Conclusions: In a computational study we evaluate the performance of the proposed procedure with real-world instances of Munich Airport. The results show that the procedure generates better solutions than a static approach. + Additional Project Focus: Determining the location of electric charging stations for a real world case. This requires preprocessing spatial data and then solving a branch and price approach solving multiple sub problems. Structure of the Problem is similar to the other project, thus points given in "Suitability" do directly apply to this project as well but uses rust and python instead of java.