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Optimization of manpower allocation by considering customer relationship management criteria and uncertainty conditions in car dealerships

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  • Mehrnaz Bathaee

Abstract

Purpose A mathematical mixed integer model was used in this research in order to optimize manpower allocation in car industry. The objective function of proposed model subjected to minimization of the maximum waiting time for customers in service queue and limitations included manpower allocation and time calculation for each service in each center. Methodology: Therefore, mathematical optimization methods were employed in this research. To solve the problem at small dimensions, BARON solver was used through GAMS software. Metaheuristic algorithms were used to solve the large dimensions of problem due to NP-hard nature of allocation problem. However, these algorithms have been designed based on the natural elements; hence, a stochastic procedure is applied to generate initial responses and to improve the process to obtained the final response. Therefore, proper comparisons should be done to make sure of accurate performance of such procedure. To this end, three metaheuristic algorithms of Genetic, Harmony Search and Gray Wolf were used to solve the final problem. Findings: According to the obtained computational results, gray wolf algorithm had the highest performance efficiency compared to other algorithms so it is more practical in solving the real numerical samples. Originality/Value: The objective function of proposed model subjected to minimization of the maximum waiting time for customers in service queue and limitations included manpower allocation and time calculation for each service in each center. We used three metaheuristic algorithms, Genetic, Harmony Search and Gray Wolf, to solve the final problem.

Suggested Citation

  • Mehrnaz Bathaee, 2021. "Optimization of manpower allocation by considering customer relationship management criteria and uncertainty conditions in car dealerships," International Journal of Innovation in Management, Economics and Social Sciences, International Scientific Network (ISNet), vol. 1(2), pages 12-27.
  • Handle: RePEc:bao:ijimes:v:1:y:2021:i:2:p:12-27:id:15
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