| Article ID: | iaor20041022 |
| Country: | United Kingdom |
| Volume: | 30 |
| Issue: | 6 |
| Start Page Number: | 415 |
| End Page Number: | 421 |
| Publication Date: | Dec 2002 |
| Journal: | OMEGA |
| Authors: | Ragsdale Cliff T., Carter Arthur E. |
| Keywords: | marketing, advertising |
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.