Revenue management for make-to-order manufacturing systems with a real-life application

Abstract

Due to successful applications of revenue management in the airline industry, in recent years, there has been a growing interest to adopt revenue management in make-to-order (MTO) manufacturing systems. Several interrelated decision problems such as order acceptance/rejection, short-term capacity planning, due date assignment, and order scheduling need to be studied simultaneously in order to manage revenues effectively in MTO manufacturing systems. Both the producer’s and customer’s requirements need to be taken into account through some negotiation mechanisms that are sensitive to the service-level reputation of the manufacturing companies. In this article, we propose a new dynamic bid price–based revenue management model that considers all of the aforementioned decision problems simultaneously. A simulation optimization approach is utilized in order to determine the best possible values of control parameters for bid price, due date assignment, and price increment/reduction mechanisms. The performance of the proposed integrated revenue management model is tested on both a hypothetical example and a real problem of a bridal gown company. The computational results show that the proposed model provides significant improvements in total revenue compared to other static and dynamic bid price policies.

Notes on contributors

Adil Baykasoğlu received B.Sc., M.Sc., and Ph.D. degrees in mechanical and industrial engineering from Gaziantep and Nottingham. He is presently a full professor and chair in the Industrial Engineering Department of Dokuz Eylül University. He has published more than 600 academic papers with more than 7,500 citations and three books and has edited several conference books on operational research, computational intelligence, and manufacturing systems design. He acts as editor and referee for many scientific journals. He is also an active member of many academic and professional institutions, including the International Society of Agile Manufacturing, Turkish Chamber of Mechanical Engineers, Turkish Fuzzy Systems Association, Turkish Operational Research Association, etc. He has received awards from TUBA, TUBITAK, METU, and several other institutions for his scientific contributions.

Kemal Subulan received his Ph.D. degree in industrial engineering from Dokuz Eylül University (DEU), Izmir, in 2016. He is presently an assistant professor in the Industrial Engineering Department of Dokuz Eylül University. His current research interests focus on fuzzy mathematical programming, fleet sizing and optimization, intermodal transportation, closed-loop supply chains, project scheduling, and revenue management.

Hülya Güçdemir is an assistant professor in the Department of Industrial Engineering at Manisa Celal Bayar University. She received her B.S., M.S., and Ph.D. degrees in industrial engineering from Dokuz Eylul University in 2010, 2013. and 2017, respectively. Her research interests include simulation modeling, simulation optimization, analytical customer relationship management (CRM), and revenue management.

Nurhan Dudaklı is a Ph.D. candidate in the Industrial Engineering Department of Dokuz Eylül University (DEU), Izmir. She is presently a research assistant in the Industrial Engineering Department of Dokuz Eylül University. Her current research interests focus on logistics, supply chain, and revenue management.

Derya Eren Akyol is an associate professor of industrial engineering at Dokuz Eylül University. She received her B.S., M.S., and Ph.D. degrees in industrial engineering from Dokuz Eylul University in 1998, 2001, and 2006, respectively. She worked as a postdoctoral researcher at the Technical University of Braunschweig and Rotterdam School of Management, Erasmus University (RSM), between March 2008 and May 2009. Her research interests include production scheduling, logistics, and revenue management.