An effective integer program for a general assembly line balancing problem with parallel workers and additional assignment restrictions. (January 2019)

• Record Type: Journal Article
• Authors: Pearce, Bryan W.; Antani, Kavit; Mears, Laine; Funk, Kilian; Mayorga, Maria E.; Kurz, Mary E.
• Is Part Of: Journal of manufacturing systems. Volume 50(2019)
• Page Start: 180
• Page End: 192
• Publication Date: 2019-01
• Subjects: General assembly line balancing -- Heuristics -- integer programming models; Manufacturing processes -- Periodicals; Production engineering -- Data processing -- Periodicals; Robots, Industrial -- Periodicals; Production, Technique de la -- Informatique -- Périodiques; Robots industriels -- Périodiques; Electronic journals; 670.42
• DOI: 10.1016/j.jmsy.2018.12.011
• Languages: English
• ISSNs: 0278-6125

Abstract

Highlights: Application of integer program and heuristic to industry-provided data in assembly line balancing. Development of an extensible effective integer program for industry-provided data. Application to complex general assembly line balancing scenarios. Abstract: The scope of the assembly line balancing problem in research is clear, with well-defined sets of assumptions, parameters, and objective functions. In application, these borders are frequently transgressed. Many of these deviations are internal to the assembly line balancing problem itself, arising from any of the physical or technological features in modern assembly lines. Other issues are founded in the tight coupling of assembly line balancing with external production planning and management problems, as assembly lines are at the intersection of multiple related problems in job sequencing, part flow logistics, worker safety, and quality. General assembly line balancing is devoted to studying the solution techniques necessary to model these applied line balancing problems. This article presents a complex line balancing problem based on the real production environment of our industrial partner, featuring several extensions for task-to-task relationships, station characteristics limiting assignment, and parallel worker zoning interactions. A heuristic, combining rank-position-weighting, last-fit-improvement and iterative blocking scheme, and an integer program that can manage multiple constraint types simultaneously, are developed. An experiment is conducted testing each of these new solution methods upon a battery of testbed problems, measuring solution quality, runtime, and achievement of feasibility. Results indicate that the integer programming model provides a viable solution method for those industries with access to commercial solvers.