A Multi-Objective and Multi-Product Advertising Billboard Location Model with Attraction Factor Mathematical Modeling and Solutions

A Multi-Objective and Multi-Product Advertising Billboard Location Model with Attraction Factor Mathematical Modeling and Solutions

Reza Lotfi (Department of Industrial Engineering, Yazd University, Yazd, Iran), Yahia Zare Mehrjerdi (Department of Industrial Engineering, Yazd University, Yazd, Iran) and Nooshin Mardani (Islamic Azad University Takestan, Tehran, Iran)
Copyright: © 2017 |Pages: 23
DOI: 10.4018/IJAL.2017010104

Abstract

Location of advertising is one of the most important factors of marketing strategy, as finding the best location to install advertising billboards can have a major impact on profitability of the entire marketing process. This paper provides a billboard location model, which can determine the optimal locations for installing such billboards. The multi-objective and multi-product model developed for this purpose has two objective functions: optimizing the sales profit minus the costs of designing and installing the billboards, and attracting most visitors through maximization of an attraction factor. The designing cost is assumed to be associated with the attraction factor. This model finds the best location of billboards based on constraint such as number of visits and sales volume. Finally, a set of small and large-scale numerical examples are solved by implementing the solution method in GAMS\Cplex solver software. To solve the large-scale variants of the problem, the genetic algorithm.
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2. Literature Review

The tasks of facility location and demand allocation fall into the domain of work of Location-allocation (LA) models, which can perform such tasks for many types of services and products (Hodgson et al., 1993). The most popular types of optimization objectives in the literature dedicated to these models are distance-minimizing or demand-covering ones. In these models, demand is often defined with points at which customers start to travel to gain access to facilities, or the points at which vehicles start to travel to serve customers. However, as Hodgson (1998) has pointed out, demands can be flow-based, i.e. based on the flow of customers traveling on a pre-determined path, instead of being focused and centered around points.

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