Hybrid optimization techniques for the workshift and rest assignment of nursing personnel

In this paper, a detailed model and an efficient solution methodology for the monthly workshift and rest assignment of hospital nursing personnel is presented. A model that satisfies the rules of a typical hospital environment based both on published research data and on local hospital requirements is designed. A hybrid methodology that utilizes the strengths of operations research and artificial intelligence was used for the solution of the problem. In particular, an approximate integer linear programming (ILP) model is firstly solved and its solution is further improved using local search techniques. Finally, a tabu search strategy that uses as its neighborhood the solution space that the local heuristics define is presented. The use of heuristics is required because one of the main user requirements involving the user preference for specific workstretch patterns is not, for efficiency reasons, explicitly modeled in the ILP. In addition, for comparison and evaluation purposes the CLP based ILOG solver is also used to solve the same problem. The inferior computational results obtained with the ILOG solver do verify the speed and efficiency of the hybrid solution approach suggested in this paper. Extensive computational results are presented together with a detailed discussion on the quality, the computational efficiency and the operational acceptability of the solutions.