Jens Clausen

Disruption management in the airline industry-Concepts, models and methods

This paper provides a thorough review of the current state-of-the-art within airline disruption management of resources, including aircraft, crew, passenger and integrated recovery. An overview of model formulations of the aircraft and crew scheduling problems is presented in order to emphasize similarities between solution approaches applied to the planning and recovery problems. A brief overview of research within schedule robustness in airline scheduling is included in the review, since this proactive measure is a natural complement to disruption management.

Vehicle routing with cross-docking

Over the past decade, cross-docking has emerged as an important material handling technology in transportation. A variation of the well-known Vehicle Routing Problem (VRP), the VRP with Cross-Docking (VRPCD) arises in a number of logistics planning contexts. This paper addresses the VRPCD, where a set of homogeneous vehicles are used to transport orders from the suppliers to the corresponding customers via a cross-dock. The orders can be consolidated at the cross-dock but cannot be stored for very long because the cross-dock does not have long-term inventory-holding capabilities. The objective of the VRPCD is to minimize the total travel time while respecting time window constraints at the nodes and a time horizon for the whole transportation operation. In this paper, a mixed integer programming formulation for the VRPCD is proposed. A tabu search heuristic is embedded within an adaptive memory procedure to solve the problem. The proposed algorithm is implemented and tested on data sets provided by the Danish consultancy Transvision, and involving up to 200 pairs of nodes. Experimental results show that this algorithm can produce high-quality solutions (less than 5% away from optimal solution values) within very short computational time.

Disruption Management in Passenger Railway Transportation

This paper deals with disruption management in passenger railway transportation. In the disruption management process, many actors belonging to different organizations play a role. In this paper we therefore describe the process itself and the roles of the different actors. Furthermore, we discuss the three main subproblems in railway disruption management: timetable adjustment, and rolling stock and crew re-scheduling. Next to a general description of these problems, we give an overview of the existing literature and we present some details of the specific situations at DSB S-tog and NS. These are the railway operators in the suburban area of Copenhagen, Denmark, and on the main railway lines in The Netherlands, respectively. Finally, we address the integration of the re-scheduling processes of the timetable, and the resources rolling stock and crew.

The manpower allocation problem with time windows and job-teaming constraints: A branch-and-price approach

The Manpower Allocation Problem with Time Windows, Job-Teaming Constraints and a limited number of teams (m-MAPTWTC) is a crew scheduling problem faced in several different contexts in the industry. The number of teams is predetermined and hence the objective is to create a schedule that will maximize utilization by leaving as few tasks uncompleted as possible. The schedule must respect working hours of the teams, transportation time between locations, and skill requirements and time windows of the tasks. Furthermore, some tasks are completed by multiple cooperating teams. Cooperating teams must initiate work simultaneously and hence this must be maintained in the schedule. The problem is solved using column generation and Branch-and-Bound. Optimal solutions are found in 11 of 12 test instances originating from real-life problems. The paper illustrates a way to exploit the close relations between scheduling and vehicle routing problems. The formulation as a routing problem gives a methodological benefit, leading to optimal solutions. A constraint on synchronization is imposed and successfully dealt with in the branching scheme.

Solving the Turbine Positioning Problem for Large Offshore Wind Farms by Simulated Annealing

The current paper is concerned with determining the optimal layout of the turbines inside large offshore wind farms by means of an optimization algorithm. We call this the Turbine Positioning Problem. To achieve this goal a simulated annealing algorithm has been devised, where three types of local search operations are performed recursively until the system converges. The effectiveness of the proposed algorithm is demonstrated on a suite of real life test cases, including Horns Rev offshore wind farm. The results are verified using a commercial wind resource software indicating that this method represents an effective strategy for the wind turbine positioning problem. The findings enable the comparison of the optimized and the grid layouts and the study of the wake differences between these configurations. It is seen that for very large offshore wind farms the difference in wake losses is negligible while, as the wind farms size reduces, the differences start becoming significant. A sensitivity analysis is also performed showing that greater density of turbines in the perimeter of the optimized wind farm reduces the wake losses even if the wind climate changes.

Disruption Management for an Airline - Rescheduling of Aircraft

The Aircraft Recovery Problem (ARP) involves decisions concerning aircraft to flight assignments in situations where unforeseen events have disrupted the existing flight schedule, e.g. bad weather causing flight delays. The aircraft recovery problem aims to recover these flight schedules through a series of reassignments of aircraft to flights, delaying of flights and cancellations of flights. This article demonstrates an effective method to solve ARP. A heuristic is implemented, which is able to generate feasible revised flight schedules of a good quality in less than 10 seconds. This article is a product of the DESCARTES project, a project funded by the European Union between the Technical University of Denmark, British Airways and Carmen (see [1]).

A hybrid algorithm for solving the economic lot and delivery scheduling problem in the common cycle case

Abstract The ELDSP problem is a combined lot sizing and sequencing problem. A supplier produces and delivers components of different types to a consumer in batches. The task is to determine the cycle time, i.e., the time between deliveries, which minimizes the total cost per time unit. This includes the determination of the production sequence of the component types within each cycle. We investigate the computational behavior of two published algorithms, a heuristic and an optimal algorithm. With large number of component types, the optimal algorithm has long running times. We devise a hybrid algorithm, which is both optimal and efficient.

Optimising the Slab Yard Planning and Crane Scheduling Problem using a two-stage heuristic

In this paper, we present the Slab Yard Planning and Crane Scheduling Problem. The problem has its origin in steel production facilities with a large throughput. A slab yard is used as a buffer for slabs that are needed in the upcoming production. Slabs are transported by cranes and the problem considered here is concerned with the generation of schedules for these cranes. The problem is decomposed and modeled in two parts, namely a planning problem and a scheduling problem. In the planning problem, a set of crane operations is created to take the yard from its current state to a desired goal state. In the scheduling problem, an exact schedule for the cranes is generated, where each operation is assigned to a crane and is given a specific time of initiation. For both models, a thorough description of the modeling details is given along with a specification of objective criteria. Preliminary tests are run on a generic setup with simulated data. The test results are very promising. The production delays are reduced significantly in the new solutions compared with the corresponding delays observed in a simulation of manual planning.

Constructing periodic timetables using MIP - a case study from DSB S-train

We describe a mathematical model to create operational timetable alternatives in DSB S-tog a/s. The model is a Mixed Integer Program implemented in GAMS and solved by CPLEX. We investigate the impact of automatic merges of lines and perform scenario analysis for a subset of the parameters in the model.

The fish industry - toward supply chain modeling.

Mathematical models for simulating and optimizing aspects of supply chains such as distribution, planning, and optimal handling of raw materials are widely used. However, modeling based on a holistic chain view including several or all supply chain agents is less studied, and food-related aspects such as quality and shelf-life issues enforce additional requirements onto the chains. In this article, we consider the supply chain structure of the fish industry. We discuss and illustrate the potential of using mathematical models to identify quality and value-adding activities. The article provides a first step toward innovative supply chain modeling aimed to identify benefits for all agents along chains in the fish industry.