Crew Rostering for the High Speed Train

At the time of writing we entered the final stage of implementing the crew rostering system Harmony CDR to facilitate the planning of catering crews on board of the Thalys, the High Speed Train connecting Paris, Cologne, Brussels, Amsterdam, and Geneva. Harmony CDR optimally supports the creation of crew rosters in two ways. Firstly, Harmony CDR contains a powerful algorithm to automatically generate a set of rosters, which is especially developed for this specific situation. As the user has some control over the objectives of the algorithm, several scenarios can be studied before a set of rosters is adopted. An important feature of the automatic roster generator is that it respects requirements, directives, and requests stemming from legal, union, and/or company regulations and/or from individual crew. Secondly, Harmony CDR provides user-interface data manipulation at various levels of detail. The user interface enables the planner to easily obtain many different views on the planning data and to manipulate the planning manually. So again, the planner gets optimal support from the system while he or she is still in control. Also, violating a requirement, directive, or request is detected and displayed, but can be accepted by the planner. In this paper we describe the crew rostering problem for the catering crews of the High Speed Train and the Harmony CDR solution in more detail.decision support systems;railways;crew rostering

A reusable iterative optimization software library to solve combinatorial problems with approximate reasoning

Real world combinatorial optimization problems such as scheduling are typically too complex to solve with exact methods. Additionally, the problems often have to observe vaguely specified constraints of different importance, the available data may be uncertain, and compromises between antagonistic criteria may be necessary. We present a combination of approximate reasoning based constraints and iterative optimization based heuristics that help to model and solve such problems in a framework of C++ software libraries called StarFLIP++. While initially developed to schedule continuous caster units in steel plants, we present in this paper results from reusing the library components in a shift scheduling system for the workforce of an industrial production plant.Comment: 33 pages, 9 figures; for a project overview see http://www.dbai.tuwien.ac.at/proj/StarFLIP

Fuzzy multi-criteria simulated evolution for nurse re-rostering

Abstract: In a fuzzy environment where the decision making involves multiple criteria, fuzzy multi-criteria decision making approaches are a viable option. The nurse re-rostering problem is a typical complex problem situation, where scheduling decisions should consider fuzzy human preferences, such as nurse preferences, decision maker’s choices, and patient expectations. For effective nurse schedules, fuzzy theoretic evaluation approaches have to be used to incorporate the fuzzy human preferences and choices. The present study seeks to develop a fuzzy multi-criteria simulated evolution approach for the nurse re-rostering problem. Experimental results show that the fuzzy multi-criteria approach has a potential to solve large scale problems within reasonable computation times

Complicating factors in healthcare staff scheduling part 2 : case of nurse re-rostering

Nurse re-rostering is a highly constrained combinatorial problem characterized with several complicating features. This paper explores recent case studies on nurse re-rostering and identifies the common complicating factors in the nurse re-rostering problem. A taxonomic analysis of complicating factors is then presented. Further, an evaluation of the complicating factors and the solution methods applied, showing the shortfalls of the approaches. A more robust and appropriate approach is realized for the complex problem. Future approaches should be intelligent, interactive, making use of a combination of fuzzy theory, fuzzy logic, multi-criteria decision making, and expert systems techniques

Crew Rostering for the High Speed Train

At the time of writing we entered the final stage of implementing the crew rostering system Harmony CDR to facilitate the planning of catering crews on board of the Thalys, the High Speed Train connecting Paris, Cologne, Brussels, Amsterdam, and Geneva. Harmony CDR optimally supports the creation of crew rosters in two ways. Firstly, Harmony CDR contains a powerful algorithm to automatically generate a set of rosters, which is especially developed for this specific situation. As the user has some control over the objectives of the algorithm, several scenarios can be studied before a set of rosters is adopted. An important feature of the automatic roster generator is that it respects requirements, directives, and requests stemming from legal, union, and/or company regulations and/or from individual crew. Secondly, Harmony CDR provides user-interface data manipulation at various levels of detail. The user interface enables the planner to easily obtain many different views on the planning data and to manipulate the planning manually. So again, the planner gets optimal support from the system while he or she is still in control. Also, violating a requirement, directive, or request is detected and displayed, but can be accepted by the planner. In this paper we describe the crew rostering problem for the catering crews of the High Speed Train and the Harmony CDR solution in more detail

A decision support system for crew planning in passenger transportation using a flexible branch-and-price algorithm

This paper discusses a decision support system for airline and railway crew planning. The system is a state-of-the-art branch-and-price solver that is used for crew scheduling and crew rostering. We briefly discuss the mathematical background of the solver, of which most part is covered in the Operations Research literature. Crew scheduling is crew planning for one or a few days that results in crew duties or pairings, and crew rostering is crew planning for at least one week for individual crew members. Technical issues about the system and its implementation are covered in more detail, as well as several applications. In particular, we focus on

A survey on constructing rosters for air traffic controllers

In this survey the state-of-the-art technology and the literature to date are discussed. In particular, we will discuss the gap in the literature concerning rostering staff to tasks by qualifications, with the inclusion of restrictions on a measure of task familiarity, which is a unique consequence of the structure of ATC operations

Complicating factors in healthcare staff scheduling part 1 : case of nurse rostering

Nurse rostering is a hard problem inundated with inherent complicating features. This paper explores case studies on nurse rostering in order identify complicating factors common in the nurse rostering problem. A taxonomy of complicating factors is then derived. Furthermore, a closer look at the complicating factors and the solution methods applied is performed. Inadequacies of the approaches are identified, and suitable approaches derived. The study recommends future methods that are more intelligent, interactive, making use of techniques such fuzzy theory, fuzzy logic, multi-criteria decision making, and expert systems

A multi-criteria approach for nurse scheduling : fuzzy simulated metamorphosis algorithm approach

Motivated by the biological metamorphosis process and the need to solve multi-objective optimization problems with conflicting and fuzzy goals and constraints, this paper proposes a simulated metamorphosis algorithm, based on the concepts of biological evolution in insects, such as moths, butterflies, and beetles. By mimicking the hormone controlled evolution process the algorithm works on a single candidate solution, going through initialization, iterative growth loop, and finally maturation loop. The method is a practical way to optimizing multi-objective problems with fuzzy conflicting goals and constraints. The approach is applied to the nurse scheduling problem. Equipped with the facility to incorporate the user’s choices and wishes, the algorithm offers an interactive approach that can accommodate the decision maker’s expert intuition and experience, which is otherwise impossible with other optimization algorithms. By using hormonal guidance and unique operators, the algorithm works on a single candidate solution, and efficiently evolves it to a near-optimal solution. Computational experiments show that the algorithm is competitive