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.
Highlights
When market dynamics cause constant changes in customer expectations, a customer-oriented approach to business strategy is required, where the value chain begins and ends with the customer [1]
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
Mathematical optimization methods were employed in this research
Summary
When market dynamics cause constant changes in customer expectations, a customer-oriented approach to business strategy is required, where the value chain begins and ends with the customer [1]. Silva et al developed a dynamic planning-based methodology for allocating human resources to software development projects Their proposed method takes into account the capabilities of the staff and the skills required for the project. Ritt et al proposed an ALWABP extension to minimize the expected cycle time of uncertain worker availability They presented this problem as a correct two-level mixed program and used local search methods to solve it [26]. Yilmaz et al focused on the problem of batch scheduling in multihybrid cell production systems (MHCMS) in a limited dual-resource (DRC) environment, taking into account the designation of skilled labor (SWA) This problem involves finding the sequence of categories in each cell, the start time of each category, and assigning staff to the operations of the categories according to the intended purpose. The new gray wolf-genetics (GGWA) algorithm is used to solve the model [39]
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