Optimal Localization of Shopping Centers Using Metaheuristic Genetic Algorithm

Document Type: Original Manuscript

Authors

1 Department of Management Science, Abhar Branch, Islamic Azad University, Abhar, Iran.

2 Faculty of Social Science, Imam Khomeini International University, Qazvin, Iran.

10.22094/joie.2019.363.0

Abstract

Efficiency and effectiveness is of importance for selection and localization. There should be regular methodology for targeting in the market by several methods. There is a necessity to have clear study for selection. In the current research, it has been studied the optimal localization at shopping centers. If there is not accuracy and validity, there will be achieved negative results for these centers such as high costs. Nowadays, these centers have turned into a part of consumer life. Today, they have penetrated consumers behavior and impacted on marketing mix. We can understand the importance of them from real shopping to window -shopping. As a meta-heuristic algorithm that inspired by natural systems, genetic algorithm has been used for problem salving as a mathematic model. The nature of genetic algorithm, which has created a relationship between humanity science and mathematics, is the reason for using it in the research. Given developed indices, Selected Iranian cities were selected for this study. Findings of the research showed that we can achieve accurate results with metaheuristic methods. The research is an applied research in terms of purpose, which is to develop applied knowledge in a certain field. 

Graphical Abstract

Optimal Localization of Shopping Centers Using Metaheuristic Genetic Algorithm

Highlights

  • Step 1: Initial population and iterative cycle in evolutionary algorithm
  • Step 2: One-point bond operator
  • Step 3: Lines with values of equal objective functions for use in the Min-Max method
  • Step 4: Diagram of target Functions towards each other.
  • Step 5: Diagram of target Functions towards each other.
  • Step 6: The coordinates of points for objective functions

Keywords


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