Service quality plays an important role in health care systems since hospitals are responsible for people's lives. This study presents an effective approach for evaluating and comparing service qualities of four hospitals. Service quality consists of different attributes and many of them are intangible and difficult to measure. Therefore, we propose a fuzzy method to resolve the ambiguity of the concepts, which are associated with human judgments. SERVQUAL model is used to evaluate the respondents' judgments of service quality and multi attribute decision making approach is implemented for the comparison among hospitals. The paper use analytical hierarchy process (AHP) for obtaining criteria weight and TOPSIS for ranking the cases.
Examination timetabling problem (ETP) is one of the most important issues in universities. An improper timetable may result in students' dissatisfaction as it may not let them study enough between two sequential exams. In addition, the many exams to be scheduled, the large number of students who have taken different courses, the limited number of rooms, and some constraints such as no conflict in a single student's exams make it very difficult to schedule experimentally. A mathematical programming model is required to formulate such a sophisticated problem. In this paper, a new binary model is developed for ETP. The novelty of the paper can be discussed in two directions. The first one is that a course can be offered more than once in a semester. If a course is requested by a few students, then it is enough to be offered once. If the number of students requesting a course is more than the maximum number of students who are allowed to attend a single class, then the course is multi-offered. The second novelty is that sharing a room for two simultaneous exams is allowed. Also, the model considers some hard and soft constraints, and the objective function is set in such a way that soft constraints are satisfied as much as possible. Finally, the model is applied in a sample department and is solved by GAMS.
In this article, a novel integrated mixed-integer nonlinear programming model is presented for designing a cellular manufacturing system (CMS) considering machine layout and part scheduling problems simultaneously as interrelated decisions. The integrated CMS model is formulated to incorporate several design features including part due date, material handling time, operation sequence, processing time, an intra-cell layout of unequal-area facilities, and part scheduling. The objective function is to minimize makespan, tardiness penalties, and material handling costs of inter-cell and intra-cell movements. Two numerical examples are solved by the Lingo software to illustrate the results obtained by the incorporated features. In order to assess the effects and importance of integration of machine layout and part scheduling in designing a CMS, two approaches, sequentially and concurrent are investigated and the improvement resulted from a concurrent approach is revealed. Also, due to the NP-hardness of the integrated model, an efficient genetic algorithm is designed. As a consequence, computational results of this study indicate that the best solutions found by GA are better than the solutions found by B&B in much less time for both sequential and concurrent approaches. Moreover, the comparisons between the objective function values (OFVs) obtained by sequential and concurrent approaches demonstrate that the OFV improvement is averagely around 17 % by GA and 14 % by B&B.
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