A Model for Optimizing Operating Profit of Industrial Companies Considering the Inefficient Allocation of Productive Resources

Abstract

Objective: The objective of the present study is to propose a model for optimizing the operating profit of industrial companies considering the inefficient allocation of productive resources. Methodology: To achieve this goal, the research gap was first identified, and based on this gap, an innovation was developed. The innovation led to the determination of the study’s objective, and based on the conducted studies, a mathematical model was proposed with the aim of maximizing operating profit while considering the inefficient allocation of productive resources. The productive resources in this model included labor, raw materials, intermediate goods, and energy. Therefore, by taking these resources and existing constraints into account, operating profit was optimized. Initially, model validation was performed by solving the model at different scales, ranging from small to large dimensions, and then the genetic algorithm’s convergence chart was obtained, demonstrating the proper performance of the algorithm. Subsequently, a parametric sensitivity analysis was conducted, which included resource parameters and cost parameters, showing a positive effect of all resource and cost parameters. Findings: Among the cost parameters, overhead costs and purchasing costs had the greatest impact, while among the positive parameters, price had the most significant effect. Conclusion: The proposed model demonstrated that optimizing operating profit in industrial companies is achievable through optimal allocation of productive resources, with overhead and purchasing costs having the greatest impact on profitability.Objective: The objective of the present study is to propose a model for optimizing the operating profit of industrial companies considering the inefficient allocation of productive resources.Methodology: To achieve this goal, the research gap was first identified, and based on this gap, an innovation was developed. The innovation led to the determination of the study’s objective, and based on the conducted studies, a mathematical model was proposed with the aim of maximizing operating profit while considering the inefficient allocation of productive resources. The productive resources in this model included labor, raw materials, intermediate goods, and energy. Therefore, by taking these resources and existing constraints into account, operating profit was optimized. Initially, model validation was performed by solving the model at different scales, ranging from small to large dimensions, and then the genetic algorithm’s convergence chart was obtained, demonstrating the proper performance of the algorithm. Subsequently, a parametric sensitivity analysis was conducted, which included resource parameters and cost parameters, showing a positive effect of all resource and cost parameters.Findings: Among the cost parameters, overhead costs and purchasing costs had the greatest impact, while among the positive parameters, price had the most significant effect.Conclusion: The proposed model demonstrated that optimizing operating profit in industrial companies is achievable through optimal allocation of productive resources, with overhead and purchasing costs having the greatest impact on profitability.