Abstract
In North America, a large percentage of infrastructure assets are deteriorating rapidly because of several reasons such as age and over capacity of consumption. Healthcare buildings and hospitals are included among vulnerable assets. Moreover, these assets have the budget constraints which makes them more vulnerable. According to Reviewing literature illuminates this fact that hospitals across Canada are engaged with deferred maintenance problems. Therefore, budgets constraints have to be managed by hospitals manager with very less impact on the primary expenditures. Solving the issue of deferred maintenance requires a high level of dedication and commitment of the maintenance human resource in hospital buildings. Resource allocation processes include several activities such as scheduling, allocation of personnel and coordination of facility manager’s team. Facility managers are under increasing pressure to prioritize maintenance work orders due to declining human resources and limited budget. Furthermore, it is necessary to optimize the cost of human resource allocation in order to achieve the desired performance. On the other hand, the resource allocation is an interactive, dynamic and complex environment of diverse and independent of facility manager’s team.
In such a complex environment, each party’s behavior may be simple, but the aggregate patterns of their interactions can be complex. Despite significant mathematical models contributions to optimize the cost of resource allocation, these approaches have some limitations such as ignorance of unforeseen events and financial losses while a facility wait for maintenance. Solving these kinds of problems is difficult for mathematical formulation.
Multi-Agent System (MAS) has viable potential in modeling that complex environment. The purpose of this research is to propose a Multi-Agent Based System (MAS) to simulate and optimize the cost of human resource allocation.
This research proposes a MAS to simulate the maintenance human resource allocation of hospitals. Furthermore, it analyzes some scenarios to achieve near optimum resource allocation cost and modify the probabilities related to work defects and poor performance.
This model studies the coordination of facility manager’s team as agents and their interaction with building component agents to minimize out of service time and maximize utilization of maintenance human resources to increase patients’ satisfaction in healthcare and hospitals. The proposed MAS model provides an opportunity for facility managers to generate a near optimal schedule and test it under a variety of conditions.
In this research, a MAS model is implemented using AnyLogic software to re-engineer facility maintenance work order processes in a department of healthcare.
