Joint Requirement of Two Multi-skill Resource Types in Multi-period Multi-site Assignment Problem

Abstract

Abstract.A classic assignment problem determines how to assign resources to tasks in the best possible way. Over the past years, the classic assignment problem has been extended and more complicated assignment models have been proposed. A multi-period multi-site assignment problem is one extension of the classic assignment problem. The number of sites and periods is increased to more than one and the decision is extended to consider assigning resources to site while concerning tasks in each site and period. Most multiperiod multi-site assignment models do not concern joint resources for operation; however, in some real-life problems, there is a case in which joint resources for performing tasks are required. In this study, we consider joint requirement of two multiskill resource types in the multi-period multi-site assignment problem and propose the mathematical model and a heuristic approach. The developed heuristic is comprised of two phases. An initial solution is generated by CPLEX in the first phase. Then the solution is improved in the second phase using proposed heuristic. This heuristic aims to allocate resources to better sites and assign resources to suitable tasks. In the computational experiment, the number of resources and the ratio of tasks requiring joint resources are varied. The result shows that the complexity of the problem highly depends on the ratio of task requiring joint resources. When all parameters are fixed except for the number of resources, there is only one range of the number of resources that makes the problem complex. For the efficiency of the algorithm, the developed heuristic can find good solutions in a short time in all ranges of the number of resources in all test problems, and optimal gaps slightly increase when the ratio of tasks requiring joint resources increases (average optimal gap of all test problems is 7.25%).

Model for allocation of medical specialists in a hospital network

“…Previous studies used LP models for human resource management in the health care sector. However, they focused only on mapping the patients’ requirements with the available physicians whereas heuristic principles should be employed in decision making as only mathematical models cannot provide solutions for physician allocation (Swangnop and Chaovalitwongse, 16 Chaovalitwongse et al, 11 and Stummer et al 20 ). On the contrary, our study takes into account specific patients’ needs according to their severity and complexity of the diseases, and attempted to allocate the best available specialists for optimal care at their respective hospitals.…”

“…For example, Chaovalitwongse et al allocated physicians, dentists, and nurses by launching mobile health services; 11 Sheu studied the allocation of transport facilities in response to disasters; 14 Vaziri et al examined the allocation of physicians for trauma patient care; 15 and Swangnop and Chaovalitwongse studied the allocation of medical personnel to many clinics and their ability to manage work time. 16 Currently, to the best of our knowledge, no research has explored specialist allocation that integrates the complexity of patients using CMI in the major diseases that affect death rates, such as cancer, heart disease, cerebral palsy, and accidental emergencies within a hospital network. This paper attempts to tackle this important problem to best manage and utilize these qualified physicians to save lives in the most effective manner.…”