Integrated crew scheduling in passenger transport industries under consideration of employee preferences

Document Type:	Conference presentation
Year of publication:	2019
Conference title:	Operations Research 2019
Location of the conference venue:	Dresden, Germany
Date of the conference:	03.-06.09.2019
Publication language:	English
Institution:	Business School > Service Operations Management (Schön 2014-)
Subject:	650 Management
Keywords (English):	Crew Scheduling , Integer Programming , Transportation
Abstract:	Due to the binary nature of the problem and the often large problem size, Crew Scheduling has always been a challenge in passenger transportation industries. Different strategies were developed to overcome the challenges; one of the most common approaches is separation of the problem into smaller problems. E.g. Airline Crew Scheduling traditionally has been separated into two planning steps: Crew Pairing, in which flights are combined into multiple-day-trips called "pairing", and Crew Assignment, in which the previously created pairings are assigned to crew members. A similar separation is used in some applications of crew scheduling for railways and other transportation industries. This separation ensures a solution in reasonable time but it sacrifices global optimality with regards to its objective cost as well as the chance to consider the employee preferences right from the start and not only in the second step - if at all. In times of staff shortage and high negotiation power of certain employee groups, consideration of employee's schedule preferences should increase employee satisfaction and thus limit employee turnover. We present an integrated crew scheduling model with the objective to minimize cost under consideration of employee preferences. Employee preferences for different schedule characteristics are estimated from a conjoint analysis and the tradeoff between employee satisfaction and cost is analyzed. Second, we provide an overview of current state of the art solution approaches specifically for integrated crew scheduling models, and suggest a column generation method to solve our problem . Third, we analyze and discuss the benefits from integration with regards to solution optimality, as well as the challenges with regard to solution times; furthermore, we provide an overview of suitable problem sizes and structures for using integration.