Dr. Kai Sun WISS Event
Please join us Wednesday, November 13 at noon in ITE 459 and online for a presentation by Information Systems Faculty Dr. Kai Sun
Lunch will be provided for those attending in-person, please use this form to RSVP.
Webex link: https://umbc.webex.com/umbc/j.php?MTID=md334cae647f1d26ae2aaa0f5e72ee228
Title: Solving process planning and scheduling problems using the method of maximum weighted independent set
Abstract: Process planning and scheduling (PPS) is an essential and practical but intractable combinatorial optimization problem in manufacturing systems. PPS seeks the process plan and schedules for critical resources to finish jobs consisting of operations that have limited resources and required sequences. One of the common objectives is to minimize the makespan, i.e., the completion time of all jobs. Due to the combinatorial complexity of PPS, the commonly used mixed-integer programming (MIP), metaheuristics, and genetic algorithms can hardly achieve satisfactory results in both quality and runtime. Previous studies have formulated such scheduling problems using graph coloring methods, but these formulations cannot be applied to generic PPS problems. Therefore, this work proposes a novel graph-based formulation for the generic PPS problem considering the minimum makespan. By representing the PPS problem as an undirected, weighted conflicting graph, the proposed method leverages the maximum weighted independent set (MWIS) to select the best set of operations and resources for each discrete time slot. To improve both solution quality and runtime, we develop an algorithm framework for the exact solutions and improved approximations of the MWIS problem. Validation on real-world PPS applications demonstrates that the graph-based approach consistently yields feasible, optimal or near-optimal solutions with improved runtimes, outperforming a leading commercial MIP solver, i.e., Gurobi. The developed method is generic and can be extended to other resource planning problems, such as wireless sensor network scheduling and timetable scheduling problems.
Bio: Kai Sun is an Assistant Professor in the Department of Information Systems at the University of Maryland, Baltimore County (UMBC). Before joining UMBC, he completed his postdoctoral training at the Alvarez College of Business at the University of Texas at San Antonio, where he collaborated with the Long School of Medicine at the University of Texas Health Science Center at San Antonio. He received his Ph.D. in Mechanical and Aerospace Engineering with a focus on Operations Research from Syracuse University in 2020. Dr. Sun’s primary research interests center around optimal and equitable resource planning with applications in healthcare and manufacturing systems, leveraging electronic health records and product lifecycle management systems. His work involves developing and applying methods in optimization under uncertainty, multi-objective optimization, graph-based models and algorithms, and data analytics and machine learning to create data-driven decision support systems.
SUPER SMASH BROS EVENT
Join us November 18, 12-2pm
ITE 469 – New Student Space
FREE PIZZA
Bring Your Controller
Participate in the HDR HACKATHON
Kick-Off Hackathon is Friday, November 22
Register by November 18
