Modeling and solving a closed-loop scheduling problem with two types of setups

Abstract

Production systems with closed-loop facilities must deal with the problem of sequencing batches in consecutive loops. This article studies a problem encountered in a production facility in which plastic parts of several shapes must be painted with different colors to satisfy the demand given by a set of production orders. The shapes and the colors produce a dual-setup problem that to the best of our knowledge has not been considered in the literature. The problem is formulated as a mixed-integer program and the limitations of this approach as a viable solution method are discussed. Two alternative solution approaches are described that are heuristic in nature: one specialized procedure developed from scratch and the other one built in the framework of commercial software. The presented computational experiments were designed to assess the advantages and disadvantages of both approaches.

Keywords:

• Closed loop scheduling
• metaheuristics
• sequence dependent setup

Notes

The facility belongs to the SMR group, which has manufacturing plants spread across the globe and specializes, among other things, in automated painting and the assembly of complete systems. SMR's business portfolio includes automotive rearview mirrors (http://www.smr-automotive.com/). Our work is based on what was observed but does not involve any formal project with SMR.Color versions of one or more of the figures in the article can be found online at www.tandfonline.com/uiie.

Datasets are available from the authors upon request.

Additional information

Notes on contributors

Subhamoy Ganguly

Subhamoy Ganguly is an Assistant Professor of Operations Management at the Indian Institute of Management, Udaipur. In the past, he has worked as a supply chain manager and as an information technology analyst. He received his undergraduate degree in Electrical Engineering from Bengal Engineering College, India, an MBA in Supply Chain Management and Finance from Michigan State University, and his Ph.D. in Operations Management from the University of Colorado Boulder. His current research interests include health care operations and supply chain management.

Manuel Laguna

Manuel Laguna is the Director of Global Initiatives and the MediaOne Professor of Management Science at the Leeds School of Business of the University of Colorado Boulder. He started his academic career at the University of Colorado in 1990, after receiving master's (1987) and doctoral (1990) degrees in Operations Research and Industrial Engineering from the University of Texas at Austin. He has performed extensive research in the interface between computer science, artificial intelligence, and operations research, resulting in over 100 publications, including four books. He has received research funding from private industry and government agencies such as the National Science Foundation, the Office of Naval Research, and the Environmental Protection Agency. He is co-founder of OptTek Systems, a Boulder-based software and consulting company that provides optimization solutions. He is the editor-in-chief of the Journal of Heuristics and has been Division Chair, Senior Associate Dean, and Interim Dean at the Leeds School of Business.