Abstract
In recent years, the use of pre-printed advertising inserts in newspapers has increased dramatically. Pre-printed inserts allow advertisers to deliver colorful, high-quality marketing material to targeted groups of consumers within the newspaper's delivery zone structure. To accommodate the increased workload associated with pre-printed inserts without negatively impacting the news deadline or delivery schedules, many newspaper companies face increasingly complex post-press scheduling decisions. This paper presents a spreadsheet model developed to represent the pre-printed insert scheduling problem in a case study of an actual medium-size newspaper company. The performance of two commercial genetic algorithm (GA) optimizers is compared on this problem. Computational testing shows the GAs develop schedules that substantially reduce the post-press production department's insert processing time.
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