Planning a TV advertising campaign: A crisp multiobjective programming model from fuzzy basic data

Omega

Volumn 38, Issue 1-2, 2010, Pages 84-94

  Perez Gladish B ^a   Gonzalez, I ^b   Bilbao Terol, A ^a   Arenas Parra, M ^a  

^a UNIVERSITY OF OVIEDO   (Spain)

^b UNIVERSITY OF VALENCIA   (Spain)

Author keywords

Ad impact; Audience expectation; Budgeting; Fuzzy techniques; Multiobjective programming; Weber and Fechner's logarithmic law

Indexed keywords

BUDGET CONTROL; COMPUTER PROGRAMMING; MARKETING; STATISTICS;

AD IMPACT; ADVERTIZING; ADVERTIZING CAMPAIGNS; AUDIENCE EXPECTATION; FUZZY TECHNIQUES; LOGARITHMIC LAW; MATURE PRODUCT; MULTIOBJECTIVE PROGRAMMING; PROGRAMMING MODELS; WEBER AND FECHN LOGARITHMIC LAW;

MULTIOBJECTIVE OPTIMIZATION;

EID: 69549126158     PISSN: 03050483     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.omega.2009.04.004     Document Type: Article

References (52)

1. Givon M., and Grosfeld-Nir A. Using partially observed Markov processes to select optimal termination time of TV shows. Omega 36 (2008) 477-485
2. Sohn S.Y., and Choi H. Analysis of advertising lifetime for mobile phone. Omega 29 (2001) 473-478
3. Godin S. Purple cow: transform your business by being remarkable (2003), Portfolio, New York
4. Paucar-Caceres A. Mapping the changes in management science: a review of "soft" OR/MS articles published in Omega (1973-2008). Omega 2009 [available online: 19 April 2009].
5. Rosbergen E., Pieters R., and Wedel M. Visual attention to advertising: a segment-level analysis. Journal of Consumer Research 24 (1997) 305-314
6. Ackoff R., and Emshoff J. Advertising research at Anheuser-Busch Inc. (1963-1968). Sloan Management Review 16 (1975) 1-15
7. Haley R. Sales effect of media weights. Journal of Advertising Research 18 (1978) 3-8
8. Simon H. ADPULS: an advertising model with wearout and pulsation. Journal of Marketing Research 19 (1982) 252-263
9. Mesak H., and Means T. Modelling advertising budgeting and allocation decisions using modified multinomial logit market share models. Journal of the Operational Research Society 49 (1998) 1260-1269
10. Ching W., Ng M., Yuen W., and Zhang S. A linear programming approach for determining optimal advertising policy. IMA Journal of Management Mathematics 17 (2006) 83-96
11. Mihiotis A., and Tsakiris I. A mathematical programming study of advertising allocation problem. Applied Mathematics and Computation 148 (2004) 373-379
12. Gensh D., and Shaman P. Models of competitive television rating. Journal of Marketing Research 17 (1980) 307-315
13. Horen J.H. Scheduling of network television programs. Management Science 26 4 (1980) 354-370
14. Rust R.T., and Echambadi N. Scheduling network television programs: a heuristic audience flow approach to maximizing audience share. Journal of Advertising 18 2 (1989) 11-18
15. Ephron E. Point of view: optimizers and media planning. Journal of Advertising Research 4 (1998) 47-56
16. Haimes Y.Y., and Steuer R.E. Research and practice in multiple criteria decision making. Lecture notes in economics and mathematical systems vol. 487 (2000), Springer, Berlin 552
17. Read W. America's mass media (1996), John Hopkins University Press, Baltimore
18. Belenky A.S., and Belenkii I. Optimization of planning an advertising campaign of goods and services. Mathematical and Computer Modelling 35 13 (2002) 1391-1403
19. Cetin E. Determining the optimal duration of an advertising campaign using diffusion of information. Applied Mathematics and Computation 173 (2006) 430-442
20. Schott B., and Whalen T. Fuzzy uncertainty in imperfect competition. Information Sciences 76 (1994) 339-354
21. Reid D.W., and Teo K.L. Optimal control problems with fuzzy system parameters. Mathematical and Computational Modelling 16 3 (1992) 3-13
22. Yager R.R. Intelligent agents for world wide web advertising decisions. International Journal of Intelligent Systems 12 5 (1997) 379-390
23. Ip R.W.L., Lau H.C.W., and Chan F.T.S. An intelligent internet information delivery system to evaluate site preferences. Expert Systems with Applications 18 (2000) 33-42
24. Ha SH. An intelligent system for personalized advertising on the internet. In: Lecture notes in computer science, vol. 3182. 2004. p. 21-30.
25. Bellman R.E., and Zadeh L.A. Decision-making in a fuzzy environment. Management Science 17 (1970) B141-B164
26. Tanaka H., Okuda T., and Asai K. On fuzzy mathematical programming. Journal of Cybernetics 3 (1974) 37-46
27. Zimmermann H.J. Description and optimization of fuzzy systems. International Journal of General Systems 2 (1976) 209-215
28. Zimmermann H.J. Fuzzy set theory and its applications (1985), Kluwer Academic Publishers, Boston
29. Sakawa M., and Yauchi K. Interactive decision making for multiobjective nonconvex programming problems with fuzzy numbers through coevolutionary genetic algorithms. Fuzzy Sets and Systems 114 (2000) 151-165
30. Słowinski R., and Teghem J. Stochastic versus fuzzy approaches to multiobjective mathematical programming under uncertainty (1990), Kluwer Academic Publishers, Boston
31. Sakawa M. Fuzzy sets and interactive multiobjective optimization (1993), Plenum Press, New York
32. Inuiguchi M., and Ramik J. Possibilistic linear programming: a brief review of fuzzy mathematical programming and a comparison with stochastic programming in portfolio selection problem. Fuzzy Sets and Systems 111 (2000) 3-28
33. Chen S.J., and Hwang C.L. Fuzzy multiple attribute decision-making, methods and applications. Lecture notes in economics and mathematical systems vol. 375 (1993), Springer, Berlin
34. Fodor J.C., and Roubens M. Fuzzy preference modelling and multicriteria decision support (1994), Kluwer Academic Publishers, Boston
35. Luhandjula M.K. Fuzzy optimization: an appraisal. Fuzzy Sets and Systems 30 (1989) 257-282
36. Sakawa M. Fuzzy sets and interactive multiobjective optimization (applied information technology) (1993), Springer, New York
37. Sakawa M. Fuzzy multiobjective and multilevel programming. In: Ehrgott M., and Gandibleux X. (Eds). Multiple criteria optimization: state of the art annotated bibliographic surveys (2002), Kluwer Academic Publishers, Boston 171-226
38. Caballero R., Ruiz F., and Steuer R.E. Advances in multiple objective and goal programming. Lecture notes in economics and mathematical systems vol. 455 (1997), Springer, Berlin
39. Steuer R.E. Multiobjective programming. In: Gass S.I., and Harris C.M. (Eds). International encyclopedia of operations research and management science (2001), Kluwer Academic Publishers, Boston
40. Dubois D., and Prade H. Operations on fuzzy numbers. International Journal of System Science 9 6 (1978) 613-626
41. Dong W., and Shah C. Vertex method for computing functions of fuzzy variables. Fuzzy Sets and Systems 24 (1987) 65-78
42. Delgado M., Vila M.A., and Voxman W. A fuzziness measure for fuzzy numbers: applications. Fuzzy Sets and Systems 94 (1998) 205-216
43. Heilpern S. The expected value of a fuzzy number. Fuzzy Sets and Systems 47 (1992) 81-86
44. Pieters R., Warlop L., and Wedel M. Breaking through the clutter: benefits of advertisement originality and familiarity for brand attention and memory. Management Science 48 6 (2002) 765-781
45. Pieters R., and Warlop L. Visual attention during brand choice: the impact of time pressure and task motivation. International Journal of Research in Marketing 16 (1999) 1-17
46. In: Branke J., Deb K., Miettinen K., and Slowinski R. (Eds). Multiobjective optimization interactive and evolutionary approaches. Series: lecture notes in computer science subseries: theoretical computer science and general issues vol. 5252 (2008), Springer, Berlin/Heidelberg
47. Luque M., Miettinen K., Eskelinen P., and Ruiz F. Incorporating preference information in interactive reference point methods for multiobjective optimization. Omega 37 2 (2009) 450-462
48. Kallberg J.G., and Ziemba W.T. Comparison of alternative utility functions in portfolio selection problems. Management Science 29 (1983) 1257-1276
49. Ballestero E., and Romero C. A theorem connecting utility function optimization and compromise programming. Operations Research Letters 10 (1991) 421-427
50. Ballestero E. Approximating the optimum portfolio for an investor with particular preferences. Journal of the Operational Research Society 49 (1998) 998-1000
51. Pratt J.W. How many balance functions does it take to determine a utility function?. Journal of Risk and Uncertainty 31 2 (2005) 109-127
52. Ballestero E., and Romero C. Utility optimization when the utility function is virtually unknown. Theory and Decision 37 (1994) 233-243