Post optimality analysis on the membership functions of a fuzzy linear programming problem
Fuzzy Sets and Systems
Nurse scheduling using constraint logic programming
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Fuzzy Sets and Systems - Fuzzy mathematical programming
An indirect genetic algorithm for a nurse-scheduling problem
Computers and Operations Research
The State of the Art of Nurse Rostering
Journal of Scheduling
A 0-1 goal programming model for nurse scheduling
Computers and Operations Research
Note: A quadratic algorithm for the 2-cyclic robotic scheduling problem
Theoretical Computer Science
Crew rostering with multiple goals: An empirical study
Computers and Industrial Engineering
Modelling interpersonal relations in surgical teams with fuzzy logic
MICAI'12 Proceedings of the 11th Mexican international conference on Advances in Artificial Intelligence - Volume Part I
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - FUZZYSS'2011: 2nd International Fuzzy Systems Symposium
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Nurse scheduling is a complex scheduling problem and involves generating a schedule for each nurse that consists of shift duties and days off within a short-term planning period. In real world applications, multiple sources of uncertainties are needed to be treated in providing higher quality schedules. This paper presents a seminal research on the application of fuzzy set theory to the nurse scheduling problem (NSP) to treat uncertainties in the target values of the hospital management and nurses' preferences. More specifically, a new multi-objective integer programming model for the NSP is developed. Then, based on this model three fuzzy goal programming models are developed using different fuzzy solution approaches. A real world application is presented to confirm the viability of the proposed models. Also, to provide the decision maker for a more confident solution set for policy decision making, a sensitivity analysis is performed. Additionally, to show the efficiency of the proposed model, it is applied to several problem instances. The paper contributes to the literature by revealing that fuzzy modeling approaches can effectively be used in the NSP in providing schedules which are more personalized and equitable for nurses, and more satisfying for hospital management.