Zhao, L.; Wang, Y. Research on Optimizing Human Resource Expenditure in the Allocation of Materials in Universities. Information2024, 15, 522.
Zhao, L.; Wang, Y. Research on Optimizing Human Resource Expenditure in the Allocation of Materials in Universities. Information 2024, 15, 522.
Zhao, L.; Wang, Y. Research on Optimizing Human Resource Expenditure in the Allocation of Materials in Universities. Information2024, 15, 522.
Zhao, L.; Wang, Y. Research on Optimizing Human Resource Expenditure in the Allocation of Materials in Universities. Information 2024, 15, 522.
Abstract
This study establishes a multivariate function model for natural human load carrying walking in some typical scenarios like college equipments and materials relocation for students. For classified materials relocation needs and constraints, we obtain the relationship between walking speed and load weight for single person, as well as the time cost for different round trips. By establishing an integer programming model with the minimum total transportation time cost and quality assurance as the objective function and the requirements of negative weight and speed as the constraints conditions, we reach the optimal item allocation methods considering time cost and shelf life were obtained. We discover that there is an approximate linear relationship between the change in natural walking speed and travel time when the load is small, thus obtaining the time cost of student transportation under different round-trip situations. The Monte Carlo simulation algorithm is used to obtain the optimal allocation scheme that meets the efficiency and quality requirements. The analysis methods and results can be used as guidance for task scheduling optimization for material relocation in educational organizations as well as commercial agencies.
Keywords
Task scheduling; integer Programming; multivariate function model
Subject
Computer Science and Mathematics, Information Systems
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
