AccScience Publishing / IJOCTA / Volume 6 / Issue 2 / DOI: 10.11121/ijocta.01.2016.00286
OPTIMIZATION & APPLICATIONS

Sales plan generation problem on TV broadcasting

Özlem Cosgun1* İlkay Gultas2
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1 Department of Industrial Engineering, Fatih University, Turkey
2 360 Management Consulting Group, İstanbul, Turkey
IJOCTA 2016, 6(2), 167–178; https://doi.org/10.11121/ijocta.01.2016.00286
Submitted: 6 January 2016 | Published: 10 July 2016
© 2016 by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution -Noncommercial 4.0 International License (CC-by the license) ( https://creativecommons.org/licenses/by-nc/4.0/ )
Abstract

Major advertisers and/or advertisement agencies purchase hundreds of slots during a given broadcast period. Deterministic optimization approaches have been well developed for the problem of meeting client requests. The challenging task for the academic research currently is to address optimization problem under uncertainty. This paper is concerned with the sales plan generation problem when the audience levels of advertisement slots are random variables with known probability distributions. There are several constraints the TV networks must meet including client budget, product category and demographic information, plan weighting by week, program mix requirements, and the lengths of advertisement slots desired by the client. We formulate the problem as a chance constrained goal program and we demonstrate that it provides a robust solution with a user specified level of reliability.

Keywords
Chance constrained goal programming
media planning
scheduling
Conflict of interest
The authors declare they have no competing interests.
References

[1] Available at:http://www.marketing.com.

[2] R.T. Rust, N.V. Echambadi, Scheduling Network Television Programs: A Heuristic Audience Flow Approach to Maximizing Audience Share. Journal of Advertising, 18- 2:11-18 (1989).

[3] J. H. Horen, Scheduling of network television programs. Management Science. 26-4:354–370 (1980).

[4] R. Rust, N. Echambadi, Scheduling network television programs: a heuristic audience flow approach to maximizing audience share. Journal of Advertising, 18:11–18 (1989).

[5] S.K. Reddy, J.E. Aronson, A. Stam, SPOT: Scheduling Programs Optimally for Television. Management Science, 44-1:83-102 (1998).

[6] H. Simon, ADPLUS: An advertising Model with Wear out and Pulsation. Journal of Marketing Research. 19:352-363 (1982).

[7] V. Mahajan, E. Muller, Advertising Pulsing Policies for Generating Awareness for New Products. Marketing Science. 5-2:86-106 (1986).

[8] G.L. Lilien, P. Kotler, K.S. Moorthy, Marketing Models. Prentice Hall, NJ, (1992).

[9] A. Mihiotis, I. Tsakiris, A mathematical programming study of advertising allocation problem. Applied Mathematics and Computation, 148:373–379 (2004).

[10] E. Cetin, S.T. Esen, A weapon–target assignment approach to media allocation. Applied Mathematics and Computation, 175:1266–1275 (2006).

[11] A. Saha, M. Pal, T. K. Pal, Selection of programme slots of television channels for giving advertisement: A graph theoretic approach. Information Sciences, 177-12:2480- 2492 (2007).

[12] S. Bollapragada, H. Cheng, M. Phillips, M. Garbiras, M. Scholes, T. Gibbs, M. Humphreville, NBC’s optimization systems increase revenues and productivity. Interfaces, 32:47–60 (2002).

[13] S. Bollapragada, M. Bussieck,and S. Mallik, Scheduling Commercial Videotapes in Broadcast Television. Operations Research, 52:679-689, (2004).

[14] V.F. Araman, I. Popescu Media Revenue Management with Audience Uncertainty. INSEAD Working Paper Series, (2008).

[15] A. Charnes, W. W. Cooper, Chance constrained programming. Management Sciences, 6:73–80 (1959).

[16] A. Charnes, W. W. Cooper, Chance constraints and normal deviates. Operations Research, 11:18-39 (1963).

[17] Charnes, A., Cooper, W.W., In: Management Models and Industrial Applications of Linear Programming, vols. 1–2. Wiley, New York. (1961).

[18] Charnes, A., Cooper, W.W., Ferguson, R., Optimal estimation of executive compensation by linear programming. Management Sciences 1, 138–151 (1955).

[19] Lee, S.M., Goal programming for decision analysis of multiple objectives. Sloan Management Review 14, 11–24 (1973).

[20] Lee, S.M., Clayton, E.R., A goal programming model for academic resource allocation. Management Science, 18 (8), B395–B408 (1972).

[21] Belaid, A., Foued, B.A., Jean-Marc, M.,

Decision maker’s preferences modeling in the stochastic goal programming. European Journal of Operational Research, 162, 610–618 (2005).

[22] Charnes, A., Cooper, W.W., Chance constraints and normal deviates. Journal of American Statistics Association, 57, 134–148 (1952).

[23] Charnes, A., Cooper, W.W., Deterministic equivalents for optimizing and satisfying under chance constraints. Operations Research, 11, 18–39 (1963).

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An International Journal of Optimization and Control: Theories & Applications, Electronic ISSN: 2146-5703 Print ISSN: 2146-0957, Published by AccScience Publishing