Healthcare Districting Optimization Using Gray Wolf Optimizer and Ant Lion Optimizer Algorithms (case study: South Khorasan Healthcare System in Iran)

Document Type: Original Manuscript

Authors

Department of Industrial Engineering, University of Kurdistan, Pasdaran Boulevard, Sanandaj, Iran

10.22094/joie.2018.766.1489

Abstract

In this paper, the problem of population districting in the health system of South Khorasan province has been investigated in the form of an optimization problem. Now that the districting problem is considered as a strategic matter, it is vital to obtain efficient solutions in order to implement in the system. Therefore in this study two meta-heuristic algorithms, Ant Lion Optimizer (ALO) and Grey Wolf Optimizer (GWO), have been applied to solve the problem in the dimensions of the real world. The objective function of the problem is to maximize the population balance in each district. Problem constraints include unique assignment as well as non-existent allocation of abnormalities. Abnormal allocation means compactness, lack of contiguous, and absence of holes in the districts. According to the obtained results, GWO has a higher level of performance than the ALO. The results of this problem can be applied as a useful scientific tool for districting in other organizations and fields of application.

Graphical Abstract

Healthcare Districting Optimization Using Gray Wolf Optimizer and Ant Lion Optimizer Algorithms (case study: South Khorasan Healthcare System in Iran)

Highlights

  • This paper deals with thepopulation districting problem in the health system.
  • This paper investigates the Healthcare districting optimizationin the health system of South Khorasan province.
  • The objective function of the problem is to maximize the population balance in each district.
  • two meta-heuristic algorithms, Ant Lion Optimizer (ALO) and Grey Wolf Optimizer (GWO), have been applied  to solve the problem

Keywords

Main Subjects


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