Although public transportation brings more and more convenience and practicality, it also presents greater safety hazards and economic concerns. How to select reasonable bus driver rostering (RBDR) for bus companies has become a pivotal resource optimization issue in public transportation by extending the Group Multirole Assignment (GMRA) model, this paper formalizes such a problem. Moreover, we propose multi-criteria decision making as a new method for driver evaluation, incorporating agent capability and satisfaction as important criteria. Additionally, in order to find the result solution more reasonably, the parameter change rules are obtained through multiple simulations. We first use the slope to find the steep drop point, and then use the variance and range to find the balance point, thereby obtaining the target parameter combination. The staged parameter selection method improves operating efficiency. Large-scale simulations indicate that the improved GMRA algorithm is suitable for different scenarios and can return multiple parameter combinations. By using this method, bus companies are able to select optimal parameter combinations in order to make diversified decisions based on transportation resources and development strategies.

Most project development processes are iterative and can be divided into multiple tasks. One person can take on multiple tasks, and one task can be assigned to multiple people. The many-to-many personnel allocation method greatly improves the efficiency of the project and saves the cost of the project. There will be two different losses in this allocation plan: the tasks undertaken by personnel are too discrete and the personnel are easily distracted when undertaking important tasks. This paper first formally models the project personnel allocation problem through the Group Multi Role Assignment (GMRA) model. Then two new constraint formulas were proposed to extend the GMRA model to reduce the loss of personnel allocation and the necessary and sufficient conditions of the extended method were proved. Subsequently, two large-scale simulation experiments were carried out to compare and demonstrate the differences between the expanded new method and the original model, and to explore the sufficient and necessary conditions to increase the speed of finding feasible solutions for the new method. Using the improved model for arranging personnel of development projects not only enables efficient many-to-many allocation but also helps reduce a lot of hidden losses in the project process.

Courier delivery is the end of the supply chain and affects the final delivery of products. Due to the promulgation of new courier delivery regulations, home delivery services have become the main choice for consumers, which has resulted in a greater workload. How to Reasonably Allocate Couriers for LEan Management (RACLEM) in supply chain optimization poses a challenge to traditional logistics. By extending the Group Multirole Assignment with Efficiency Degradation (GMRAED), this paper formalizes the problem. Moreover, we propose a quantitative calculation method of efficiency degradation based on Amdahl's law, taking region similarity and the number of tasks as important criteria, and compare the performance of different personnel arrangements. Additionally, compared with the brute force algorithm, we combine GMRAED and Genetic Algorithm (GA) to create a practical solution. Large-scale simulation experiments demonstrate that the genetic algorithm significantly shortens the solution time, and the lowest experimental accuracy is 99.407%. By using the above method, decision-makers are able to assist companies optimize personnel resource allocation, minimize personnel waste, and improve the performance of courier delivery within a shorter timeframe.